Jobs AI

We are a Ukrainian multiproduct company that creates database development and management tools, connectivity solutions, productivity tools, and data services for more than 500.000 clients from 120 countries. Among our clients, you can find such legends as Microsoft Corporation, Oracle America, IBM, Intel, and many more companies that deserve their place in the Fortune 100 and Fortune 500.

Since 1997, we have been streamlining data workflows for professionals and teams with our intuitive and efficient software products. We’re committed to enhancing our customers’ experience across the globe by minimizing data-related tasks and enabling them to focus on more inspiring goals. Whether it’s Fortune-100 companies or individuals, we provide a customer-centric approach, delivering high-quality solutions and exceptional support.

Driven by passion, we play a substantial role in shaping the future of data management.

Product that needs your engagement 

You will be at the heart of building a new generation web-based application fully powered by AI technologies. This product is envisioned as a cutting-edge tool that redefines how professionals interact with complex data and workflows. We’re not just adding AI features into an existing app — we are designing an AI-first experience from the ground up, where automation, personalization, and intelligence are embedded in every interaction. The application will combine scalability, intuitive UX, and deep AI integration to create a solution that is both technically robust and delightful to use.

Your future team of professionals 

You will join an ambitious and growing team that values collaboration, ownership, and thoughtful engineering. You will work closely with Backend and Frontend Engineers, a Product Manager, and a QA Engineer, contributing to the development of the product and helping shape its technical direction as the team continues to grow.
 

Your future challenges & opportunities

Opportunities

• Direct involvement in the launch of a new product, with real impact on architecture and technical decisions.
• Hands-on experience building DWH integrations and MCP-based AI pipelines — one of the most in-demand skill sets in 2026.
• Work at the intersection of backend engineering and AI, expanding expertise beyond traditional .NET development.
• Opportunity to define integration patterns and technical standards from the ground up, rather than maintaining legacy code.

• Exposure to the full product lifecycle: from data modeling and API design to production deployment and optimization.

   

Challenges

• Proactively learn and adopt MCP, a recently introduced standard, keeping pace with a fast-evolving ecosystem.
• Design and implement DWH integrations with careful data modeling and schema planning — early mistakes can be costly.
• Balance product launch deadlines with the need to maintain clean, scalable, and maintainable architecture under pressure.
• Work across multiple technical domains simultaneously: data pipelines, API development, and AI tool integration.

• Validate and responsibly apply AI-assisted development tools, avoiding over-reliance on generated output.

   

Impact you will make 

• Design, build, and maintain scalable back-end services and APIs using C# and the .NET ecosystem, ensuring high performance, reliability, and maintainability.
• Ensure security, performance, and reliability across server-side components by applying SOLID principles, established design patterns, and back-end best practices.
• Write clean, testable, and well-documented code that meets team coding standards and supports efficient code reviews.
• Collaborate closely with front-end developers to design and integrate RESTful or GraphQL APIs that power seamless user experiences.
• Participate in code reviews and contribute to the continuous improvement of team engineering practices and standards.
• Optimize application performance, database queries, and system throughput to handle high-load environments efficiently.

• Conduct thorough testing and debugging to deliver high-quality, production-ready software.

   

Skills we are looking for 

• At least 5 years of experience as a .NET Developer (ASP.NET Core, Entity Framework Core), preferably in a tech-focused environment.
• Higher education in Computer Science, Information Technology, or a related field (relevant certifications are a plus).
• Deep understanding of software principles: SOLID, IoC, OOP, design patterns, and client/server architecture.
• Experience designing and building RESTful APIs and microservices.
• Experience with version control using Git and collaborative workflows (branching, pull requests, reviews).
• Familiarity with authentication concepts and secure application development (OAuth2, JWT).
• Experience with relational databases and ORM tools (SQL Server, PostgreSQL, Entity Framework Core).
• Experience with testing frameworks (xUnit, NUnit, Moq).
• Knowledge of Docker/docker-compose and basic CI/CD processes.
• Performance optimization skills: profiling .NET applications, identifying bottlenecks, and improving throughput.
• Ability to effectively use AI-assisted development tools (GitHub Copilot, ChatGPT, etc.), understand their limitations, and responsibly apply them in the development workflow.

Benefits you get

• Maintain your work-life balance

Manage your own working hours with our flexible schedule

19 days of annual vacation granted on a pro-rata basis

No overtimes required

• Hybrid type of cooperation

Whether you prefer to work remotely in the comfort of your home office or from one of our 4 offices, you can still take part in increasing the world`s awareness about quality Ukrainian products from any part of the world

• Stay healthy

Medical insurance from one of the top insurance companies in Ukraine with a wide range of included services, as well as special programs for relatives; and special options for those who live abroad.

15 working days of sick leave per year — because your health is a priority.

• Grow with us

In-house English courses — increase your proficiency through our online courses and speaking clubs with a native speaker

Online learning activities — workshops, lectures, and webinars to enhance your leadership, management, and self-awareness skills

Experience exchange — we are proud of our team of professionals who gladly share their deep expertise in all kinds of fields with the rest of the team

Promotions, rotations, and transitions — when you believe your skills could benefit a different role or team.

• Stand with Ukraine!

We have an active pro-Ukrainian position, and that means we help our army, our servicemen, and their families not only through constant donations and volunteering, but also through our military leave policy, special health insurance options, and financial help

We are a perfect match if you share our values

We are professionals in our field.

We know how to turn up our professionalism to the maximum, because we are experts who enjoy solving complex tasks.

We know how to focus on the product, think big, and at the same time delve deep into the details.

We create a calm and friendly atmosphere within the company.

We value the freedom of open and transparent communications.

Radical honesty is embedded in the foundation of our culture.

We are open to new things and constantly develop and practice regular knowledge sharing, which helps us evolve continuously.

Most importantly, the company creates an environment where we can fulfill our potential upon a solid foundation.

Our Hiring Process

• Recruitment Interview
• Technical Interview
• Offer Call

We strive to ensure transparency and openness in the hiring process, and we understand the importance of providing timely feedback. If your resume meets the job requirements, we will contact you to clarify details and schedule an interview within 2 weeks after your application is submitted.

The timeframe for feedback between interview stages may take up to 2 weeks.

HBDCard is a crypto / fintech product focused on making crypto payments simple and practical for everyday use.
 

We are looking for a hands-on AI Social Media & Growth Manager who can build and manage our social media presence, create high-quality content using modern AI tools, and help grow the HBDCard brand.
 

This is not a role for someone who only schedules posts or follows a basic monthly content plan.
 

We need someone who understands social media culture, knows how to use AI tools at a high level, can move fast, test ideas, follow trends, and turn them into engaging content.
 

Responsibilities:
 

• Manage HBDCard social media channels: X / Twitter, Instagram, TikTok, LinkedIn, Telegram
   
• Build and execute the social media content strategy
   
• Create short-form videos, graphics, carousels, memes, posts, threads, and other content
   
• Use AI extensively in the content production process
   
• Follow crypto, fintech, payments, AI, and social media trends
   
• Quickly turn relevant trends and market events into HBDCard content
   
• Write strong English copy, hooks, captions, and CTAs
   
• Test different content formats, hooks, visuals, and creative approaches
   
• Analyze content performance and continuously improve based on data
   
• Grow engagement, followers, website traffic, sign-ups, and customer acquisition
   
• Engage with relevant crypto, fintech, and Web3 communities
• Identify potential collaborations, influencers, creators, communities, and distribution opportunities
   

AI tools:
 

You should be comfortable working with modern AI tools such as ChatGPT, Claude, Midjourney or other AI image generators, Kling, Google Veo, Seedance, Runway, ElevenLabs, HeyGen, CapCut, and similar tools.
 

We do not expect you to use every tool. What matters is that you understand how to combine AI tools into an efficient workflow and consistently produce high-quality content.
 

Requirements:
 

• 2+ years of experience in social media, content, growth, or a related role
   
• Strong practical experience with AI content-generation tools
• Strong understanding of Instagram, TikTok, X / Twitter, LinkedIn, and short-form video
   
• Good visual taste and understanding of modern social media content
   
• Ability to create content independently without requiring a designer for every post
   
• Strong written English
   
• Ability to write strong hooks and natural copy that does not feel generic or obviously AI-generated
   
• Understanding of social media analytics and content performance
   
• Ability to work independently and take ownership of the social media direction
   
• Fast execution and willingness to experiment
• Ability to identify trends and quickly turn them into relevant content
   

Big advantage if you have experience with:
 

• Crypto / Web3
   
• Fintech
   
• Crypto cards or payment products
   
• Growing X / Twitter accounts in the crypto space
   
• Telegram communities
   
• Organic social media growth
   
• Influencer or creator collaborations
   
• Short-form video production
   
• Video editing or motion design
   
• Basic paid social / Meta Ads / TikTok Ads
   
• Community management
   

We are not looking for someone whose main workflow is simply creating a fixed number of posts per month and scheduling them.
 

We want someone who actively looks for opportunities, understands trends, generates ideas, produces content, tests it, analyzes results, and improves quickly.
 

Working format:
 

• Full-time
• Long-term cooperation
• Direct communication with the HBDCard team
   

How to apply:
 

Please send:
 

1. A short introduction about yourself
2. Links to social media accounts or brands you have managed
3. Examples of content you personally created
4. Examples of AI-generated content you created
5. The AI tools you use regularly
6. Your experience with crypto, fintech, or Web3, if any
7. Your expected monthly salary
    

Please also answer:
 

If you joined HBDCard tomorrow, what would you do during your first 30 days to grow our social media presence?

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
  This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

   

• Responsibilities:

  - Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
  - Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
  -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
  -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
  -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

   

• Mandatory Skills Description:

  - 2 month project with posibility of extentention

  - Python — strong hands-on Python development experience for building tools and automation
  - GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
  - Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
  - AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
  - GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
  - Automation frameworks — experience designing and building automation frameworks/tooling from scratch
  - Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
  - Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

   

• Nice-to-Have Skills Description:

  Experience in financial domain

   

• Languages:
  • English: C2 Proficient

Project Description:

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

Responsibilities:

- Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
- Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
-Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
-GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
-Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

Mandatory Skills Description:

- Python — strong hands-on Python development experience for building tools and automation
- GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
- Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
- AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
- GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
- Automation frameworks — experience designing and building automation frameworks/tooling from scratch
- Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
- Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

Nice-to-Have Skills Description:

Experience in financial domain

• This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
  During this Mobilisation Phase, you'll work jointly with engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
  The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.

   

• Responsibilities:

  -Target-state architecture design — define and own the target-state AWS architecture across compute, data, and orchestration layers
  -HLD/LLD ownership — produce and own High-Level Design and Low-Level Design documentation for migration workloads
  -ARB submissions — prepare and present architecture proposals to the Architecture Review Board for approval
  -Technical decisions — make and document key technical decisions across the migration program, balancing trade-offs (cost, performance, scalability)
  Pattern definition — define reusable architecture and migration patterns for use across teams/pods
  -Agentic AI framework architecture — design the architecture for the Agentic AI migration framework, including its integration with the broader technical landscape

   

• Mandatory Skills Description:

  - 5+ years experience

  - 2 month project with posibility of extentention
  - hands-on experince with AWS Migration
  - AWS Glue, Step Functions, Lambda, EventBridge — deep hands-on experience designing solutions using these core AWS services
  - IaC (Terraform) — strong experience defining and managing infrastructure as code with Terraform
  - Data platform architecture — proven experience architecting data platforms (data lakes, warehouses, pipelines) at scale
  - PySpark — hands-on experience with PySpark for large-scale data processing
  - CI/CD — experience designing and implementing CI/CD pipelines for infrastructure and data workflows
  - AI/ML frameworks — working knowledge of AI/ML frameworks and their application within architecture design
  - GitHub Copilot — practical experience using GitHub Copilot within development/architecture workflows

   

• Nice-to-Have Skills Description:

  - AWS certification (Data Analytics Specialty or Solutions Architect)
  - Experience with BI tools (QuickSight, Tableau, Power BI)
  - Infrastructure as Code experience (Terraform/CloudFormation)
  - Industry experience relevant to your business
  - Exposure to streaming data (Kinesis) or ML pipelines (SageMaker)
  - experince in financial domain

   

• Languages:
  • English: C2 Proficient

This is a strategic data engineering engagement with our client to architect and plan the migration of their entire data processing and ETL estate from Matillion to AWS Glue — a foundational shift in how one of the world's largest financial market infrastructure companies handles its data pipelines.
During this Mobilisation Phase, you'll work jointly with client's engineering teams to reverse-engineer the existing landscape, design the target-state architecture across every layer (infrastructure, data processing, workflows, dependencies, and operating model), and build the detailed delivery blueprint that will greenlight the full-scale migration.
The work is technically rich and highly collaborative: you'll review and validate job inventories spanning hundreds of ETL workflows, define reusable migration patterns and templates, design a validation and reconciliation framework, run a proof-of-concept to stress-test the approach, and navigate client's rigorous internal governance — from Architectural Significance Assessments through Architectural Review Boards to a formal Gate 1 decision.
This is the kind of engagement where your recommendations directly shape a multi-phase, multi-million-pound programme: the target-state framework you produce here becomes the blueprint that a larger delivery team will execute against. Perfect opportunity for combining deep data engineering knowledge with architecture leadership, stakeholder influence, and structured delivery planning inside a Tier 1 financial services environment

• Responsibilities:

  - Agentic AI Migration Framework development — design and build an agentic AI framework to automate and accelerate migration workflowsж
  - Pattern library build — develop and maintain a library of reusable migration patterns/templates for common conversion scenarios;
  -Automated conversion pipeline — build pipelines that automatically convert/transform code and configurations (e.g., Matillion jobs) as part of the migration process;
  -GitHub Copilot integration for code generation — integrate GitHub Copilot into the migration workflow to accelerate code generation and conversion tasks;
  -Support factory pods — provide technical support, tooling, and troubleshooting to migration factory pods executing migrations at scale

• Mandatory Skills Description:

  - Python — strong hands-on Python development experience for building tools and automation
  - GenAI/LLM integration — experience integrating GenAI/LLM capabilities into applications, workflows, or tooling
  - Prompt engineering — hands-on experience designing, testing, and optimizing prompts for LLM-based tools
  - AWS Bedrock — hands-on experience with AWS Bedrock for building GenAI-powered applications
  - GitHub Copilot — practical experience using and/or integrating GitHub Copilot into development workflows
  - Automation frameworks — experience designing and building automation frameworks/tooling from scratch
  - Testing — strong experience with test automation and validation frameworks to ensure conversion accuracy
  - Matillion JSON parsing — experience parsing, interpreting, and transforming Matillion job definitions (JSON format)

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We're looking for an AI Architect to become our lead technical expert for client AI solutions and to help stand up our AI Competence Centre and internal AI Lab.

This is a client-facing technical role first, with a build-and-lead dimension. Expect roughly 60% solution architecture and pre-sales engineering for enterprise clients, and 40% establishing the AI Lab and mentoring engineers. You'll technically lead and raise the bar for the team - this is a technical leadership role, not a people-management line.
Reports to: Head of AI.

Requirements

• Experience & seniority. 5+ years in software, data, or ML engineering, including 3+ years delivering ML/AI in production and 2+ years in a client-facing architect or technical lead capacity.
• Cloud & AI infrastructure. Production-level experience on Google Cloud Platform, especially the Vertex AI suite, plus integrating third-party model providers such as Anthropic.
• GenAI engineering. Strong hands-on knowledge of RAG, agentic workflows, orchestration frameworks (LangChain, LlamaIndex), vector databases, and prompt/context engineering.
• Production & MLOps. Hands-on with the ML lifecycle, CI/CD for models, automated deployment, and cloud cost management - including right-sizing models (lighter vs. heavier) to control spend.
• Evaluation, guardrails & observability. Practical experience building LLM evaluations, guardrails, and monitoring for accuracy, safety, latency, and cost in production.
• AI governance & security. Familiarity with data governance, model risk, and EU regulation (EU AI Act, GDPR) as it applies to enterprise AI — we're primarily EU-based.
• Pre-sales & client experience. Proven experience presenting to enterprise clients, scoping technical projects, and translating complex AI concepts into clear business value.
• Technical leadership. Experience guiding engineers, reviewing architecture and code, and raising team capability.
• Languages. Native Ukrainian — required, as you'll run Ukrainian-language pre-sales — and strong English (B2+/C1 minimum).

• Mindset & agility. An intrapreneurial drive to build an AI Lab from scratch inside an established business, plus the agility to move smoothly between client pre-sales and deep technical architecture.

   

Responsibilities

• Solution architecture. Design and own end-to-end AI systems for strategic enterprise clients - reference architectures, data and retrieval pipelines, agentic layers, and integration with existing enterprise systems - with a clear path from prototype to scalable, secure, observable production.
• Pre-sales & consulting. Partner with sales to qualify and win AI opportunities: run technical discovery, scope solutions, size effort and cost, and translate AI into business value, ROI, and risk for C-level stakeholders.
• Technical leadership & mentorship. Set architecture and engineering standards, run design and code reviews, and level up engineers across the AI practice.
• AI Lab & R&D. Stand up and run the internal AI Lab - rapid client prototypes and cost-effective internal AI tooling - with a clear bar for what graduates into production.
• Partner collaboration. Work with our core AI partners (Google Cloud / Vertex AI, Anthropic) to build joint solutions, access early capabilities, and shape our technical roadmap.
• Governance, security & cost. Build guardrails, evaluation, and observability into every solution; keep architectures compliant (EU AI Act, GDPR) and cost-aware through right-sized model selection.

Would be a plus

• Google Cloud Professional Machine Learning Engineer and/or Professional Cloud Architect certification.
• Hands-on enablement or certification with Anthropic and Vertex AI generative-AI stacks.
• Direct experience mapping solutions to the EU AI Act risk framework.
• Fine-tuning, distillation, or model-optimization experience.
• Production experience with voice/multimodal AI (e.g., ElevenLabs) or AI-assisted engineering tooling (e.g., Cursor).
• Contributions to the open-source GenAI ecosystem.

Work conditions

• Flexible Work Format: Work remotely, allowing you to balance your professional and personal life efficiently.
• Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud and AI solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
• International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
• Global Exposure: Expand your expertise by engaging with international markets across the EMEA and CEE regions.
• Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.
  
  When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
  Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

Backend Software Engineer (Python, AI)
 

Requirements:
- 6+ years of experience in backend design and development of production-grade applications.
- Strong experience with Python
- Solid experience with databases, preferably SQL
- Experience working with large-scale systems
- Experience with AI orchestration frameworks such as LangChain or LlamaIndex, or experience integrating third-party AI APIs such as OpenAI or Anthropic.
- Knowledge of networking infrastructure.
- Cybersecurity experience - a strong advantage.
- Ability to learn quickly and adapt to new technologies.
- Strong teamwork and collaboration skills.
 

Responsibilities:
- Take full ownership of features, from product design through deployment, including end-to-end feature architecture.
- Plan, design, and develop systems with complex performance and scalability requirements.
- Design, maintain, and contribute to the company’s code infrastructure.
- Design, build, and maintain robust, scalable server-side architecture.
- Integrate with Large Language Models (LLMs) and vector

About the client

Our client is a leading European online car marketplace, connecting car buyers and sellers across the continent. The platform serves over 30 million monthly users and operates across 18 countries, making it one of the largest and most trusted digital marketplaces for vehicles in Europe.

About the role

As a Senior Data Scientist, you will be a key contributor within the client's global Data Science organization, shaping the AI and machine learning systems that sit at the core of marketplace platforms across Europe and Canada. You will design, build, and operate machine learning and GenAI systems that run in production and matter to the business — working on complex, ambiguous problems, exercising strong technical judgment, and taking responsibility for outcomes, not just models.

While this is a hands-on role, you will also influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed.

Responsibilities:

• Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement.
• Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability.
• Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes.
• Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints.
• Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems.
• Raise the bar for engineering practices across the Data Science organization and influence technical direction beyond your own projects.

Requirements:

• 5+ years of experience building and owning production ML systems end-to-end in a real-world environment.
• Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field.
• Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production.
• Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale.
• Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations.
• Ability to influence technical decisions through clear judgment and collaboration, not formal authority.
• Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback.
• Strong sense of ownership and accountability for outcomes, with a pragmatic approach to trade-offs and delivery.
• Excellent verbal and written English skills.

Nobody taught our generation how money works.

We earn, we spend, we mean to save  and somehow the year ends the way it started. Financial literacy is the one thing nobody teaches you, and the one thing everyone assumes you already have.

GRO is an AI powered financial companion for exactly those people: Gen Z and Millennials that teaches you money instead of just tracking it.

https://www.joingro.com/

Our mission is to teach the next generation what nobody taught ours.

Our stage: Pre-seed closed, public beta and launch before the end of this year. 

WHO YOU'D BE JOINING

Four founders. 

Our CTO is building the Companion - the LLM layer, the memory, the architecture intent.  You'd be the person who turns it into something people can actually hold: the app, the backend, the money layer, the release pipeline.

First engineer in, which means you're not inheriting anyone else's decisions. You're making them. Hands-on all the way through beta  and if you want to grow into leading the team you help hire, that path is open and it's yours to take.

First six months: a native app live on both stores, a backend that's secure and observable, and a release process the team can run without you in the room. Then: open banking integration, SOC 2 groundwork, and the kind of engineering a Series A technical diligence doesn't flinch at.

WHAT'S YOURS

— The app. React Native / Expo. Performance, offline behaviour, native builds, OTA.

— Store releases. App Store and Google Play, signing through post-launch.

— Backend and the money layer. NestJS, Prisma, Postgres, OpenAPI. Idempotency, audit trail, tenant isolation.

— Platform, security and compliance. Shared with the CTO, executed by you — CI/CD, IaC, secrets, observability, GDPR, SOC 2 path, QCB readiness.

— The boundaries that matter. The deterministic money core and the education-not-advice line, enforced in code rather than in disclaimers.

WHO WE'RE LOOKING FOR

— You've shipped and operated a consumer financial product. Real users, real money, real incidents.

— Your React Native or Expo apps are live on both stores, and you handled signing, review and everything after launch.

— Node and TypeScript backend depth is real - NestJS or equivalent, Postgres, contract-driven.

— CI/CD, Terraform, secrets and observability are just how you work. Not a task you get to later.

— Security-first by instinct: auth hardening, idempotency, audit trails, PII, threat modelling.

— You're comfortable with a clean line: the CTO owns the Companion and the architecture intent, you own everything around it. That takes trust in both directions.

— English C1 or above. It's our working language.

NICE, NOT REQUIRED

Open banking aggregators (Tarabut, Plaid or similar) - a dedicated expert owns that bridge, you'd partner with them. SOC 2 or ISO 27001 audits. Cost and eval discipline for LLM-powered apps.

THE SETUP

Remote. Full-time. A path to founding team member, working directly with the CTO. Compensation and equity could be discussed directly.

We're small enough that you'll know why every decision got made, and early enough that a part of them will be yours.

About

We’re looking for a senior ML/AI Engineer to build Stream, a new conversational interface. As an ML/AI engineer, you will architect, build, and deploy a new interface which spans voice, audio, and agentic control. This role is perfect for someone who cares deeply about real-world ML deployment and low-latency voice interactions.

Responsibilities

• Design and improve user-facing experiences, including voice, audio, and agentic control.
• Develop, evaluate, and deploy models spanning cloud models to resource-constrained on-device settings
• Optimize inference pipelines for latency, reliability, and concurrency

• Work closely with other ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products

   

Qualifications

• 4+ years in artificial intelligence or machine learning applications
• Experience shipping ML-based products is required
• Experience in large-language models is required
• Experience in audio / voice ML is a major plus
• Comfortable writing production-grade software
• Passion for human-computer interaction

T H E  R O L E
Own the intelligence layer of Rx360 — the models that turn continuous sensor and medication data into a working understanding of each individual we serve, and turn that understanding into actions that help them stay independent. You will set the ML architecture, build the longitudinal modeling stack from raw signal through to user-facing recommendation, and define how our models and our conversational companion work together.

W H AT Y O U ' L L D O
Own the ML architecture for personalized health intelligence — per-user baselines, N-of-1 and hierarchical models, and the strategy for learning from one individual's history rather than a population mean.
Build the digital biomarker stack on raw wearable signal: gait and cadence, sit-to-stand and postural transitions, activity classification, sleep and circadian structure, and cardiovascular trend from IMU and PPG streams.
Design change detection and event-association models that link medication starts, dose adjustments, and adherence gaps to downstream behavioral shifts — with defensible handling of confounding, lag structure, and multiple comparisons.
Turn a detected change into a recommendation: what to surface, to whom (the individual, family, pharmacist, or provider), with what urgency — and when the right answer is to say nothing.
Build the data and training infrastructure that carries high-frequency time-series from device ingestion through feature generation, training, serving, and monitoring.
Own evaluation. Offline benchmarks, labeled ground truth from pilot cohorts, calibration and drift monitoring, and the false-positive budget that decides whether people trust what we tell them.
Ground our conversational companion in real signal. Our AI companion runs on a large language model inside our
HIPAA-compliant cloud environment; you will connect it to per-user model output and own the evaluation and post- training work that keeps its guidance accurate, useful, and safe.
Push inference to the edge where latency, privacy, or battery demand it, working directly with the firmware and hardware teams on what runs on the band versus in the cloud.
Direct AI coding agents to accelerate implementation while holding a rigorous quality bar — the way the rest of our engineering team works.
Partner with clinical collaborators, including our university pilot, to design studies that produce the labeled data these models actually need.
Set technical direction and raise the bar for ML across the team.

R E Q U I R E D
6+ years in machine learning, including systems you have shipped to real users and operated in production — not only research or prototypes.
Deep experience with time-series or sensor data: physiological signals, IMU / accelerometry, or comparable high- frequency multivariate streams.
Demonstrated work in individual-level modeling — per-subject baselines, hierarchical or Bayesian methods, anomaly and change-point detection, or models that adapt as data from a single person accumulates.
Strong applied statistical judgment. You can separate a real effect from a coincidence in observational data, and you know exactly where a causal claim stops being defensible.
Production-grade Python and PyTorch (or equivalent). You write software other engineers are willing to maintain.
Ownership of the full lifecycle: data pipelines, training infrastructure, deployment, monitoring, and retraining.
Experience with large-language-model evaluation and post-training — grounding and retrieval, structured output, eval harnesses, and guardrails.
Cloud-native ML at production scale (AWS preferred).
Fluent use of AI development tools (Claude Code, Cursor, Copilot, or equivalent) with the domain depth to catch where generated code fails silently.
Clear, direct communication. You can set direction across firmware, backend, mobile, design, and clinical stakeholders.

N I C E T O H AV E
Wearables, digital biomarkers, gait analysis, fall risk, or human activity recognition.
Self-supervised or foundation-model approaches for wearable time series, and comfort working under real label scarcity.
Causal inference on observational data — interrupted time series, difference-in-differences, or synthetic control.
Medication-effect modeling: polypharmacy, adherence, or PK/PD intuition.
On-device and edge ML — quantization, distillation, TinyML, inference under a power budget.
Regulated environments: HIPAA and PHI handling, model governance, or the general-wellness boundary.
Clinical research collaboration and IRB-governed data.
Voice or audio ML.

W H Y T H I S R O L E I S D I F F E R E N T
G R E E N F I E L D
You are defining the intelligence layer, not maintaining someone
else's. The architecture decisions are yours to make.
R E A L S I G N A L
Continuous, longitudinal, multi- stream data from a device we build
ourselves — with the firmware team a message away.
I T M AT T E R S
A model that catches a medication effect three days early changes
whether someone keeps living in their own home.

H O W W E W O R K
Mission comes first.
The work has real impact on people's lives. We take that
responsibility seriously.
Thoughtful technology.
Technology should simplify life, not complicate it.
Respect for independence.
The people we build for value autonomy and dignity.
Everything we create reflects that.
Curiosity.
We encourage questions, experimentation, and new ways
of thinking.

A B O U T R X 3 6 0
Rx360 is a wellness platform for older adults who want to keep living on their own terms — and for the families, pharmacists, and providers around them.
The wearable is a wrist-worn band we design in-house, carrying a PPG sensor for cardiovascular signal, a six-axis IMU for motion, gait, and posture, and on-device fall detection. The iOS and Android apps give the individual a plain- language view of their own day and their medications, and open a shared circle of care to the family members they choose to include.
Rx360 is a U.S. company headquartered in Los Angeles, California, with a distributed engineering team. Hardware, firmware, mobile, backend, and machine learning are all in-house.

About ByChat FinOps

ByChat FinOps is a production-ready B2B AI platform that helps organizations understand, analyze, and optimize cloud infrastructure costs across AWS.

Our platform combines cloud billing data with Generative AI, enabling users to ask natural language questions such as:

• Why did our cloud costs increase this month?
• Which services generate the highest expenses?
• Will we exceed our budget next quarter?
• Where can we reduce infrastructure costs?
   

Behind the scenes, intelligent LLM Agents work with cloud APIs, read-only SQL queries, billing datasets, forecasting models, anomaly detection algorithms, and FinOps analytics to deliver accurate, explainable business insights.

ByChat FinOps is an actively growing production product where AI reliability, security, scalability, and measurable business value are our highest priorities.
 

About the Role

We are looking for a Senior / Lead ML Consultant to support our engineering team on a part-time basis and provide expert guidance on the architecture, development, evaluation, and optimization of our AI/ML capabilities.

This is primarily an advisory and technical leadership role rather than a full-time hands-on engineering position.

You will work closely with our AI/ML engineers and technical team, review existing approaches and processes, identify potential risks and inefficiencies, and provide practical recommendations for improving the quality, reliability, and efficiency of our AI systems.

We expect you to act as a senior technical advisor and sparring partner for the team, helping us validate technical decisions and ensure that our ML/LLM practices meet production-grade standards.
 

What You'll Do

Your responsibilities will include:

• Review the architecture and implementation of our AI/ML and LLM-based solutions.
• Provide regular technical feedback to AI/ML engineers and help validate key engineering decisions.
• Review existing ML/LLM development processes and recommend improvements.
• Evaluate the effectiveness, reliability, and scalability of current AI workflows.
• Advise the team on the design of LLM Agents, sub-agents, tool calling, structured outputs, and agentic workflows.
• Review approaches to prompt engineering, context management, guardrails, validation, retries, and hallucination mitigation.
• Assess and improve LLM evaluation methodologies, automated testing, golden datasets, and quality metrics.
• Advise on AI observability, tracing, monitoring, and production quality control.
• Review Text-to-SQL approaches and help ensure safe and reliable interaction with financial datasets.
• Provide guidance on anomaly detection, forecasting, and other ML components used within the platform.
• Identify performance bottlenecks and opportunities to optimize LLM latency, token usage, infrastructure usage, and operational cost.
• Help the team evaluate new AI/ML technologies, frameworks, models, and architectural approaches before introducing them into production.
• Participate in technical discussions and architecture reviews for complex AI-related features.
• Mentor engineers and help strengthen the team's ML/LLM engineering practices.
• Help establish practical engineering standards and best practices for building production-grade AI systems.
   

What We Expect

Must Have

• Strong senior-level commercial experience in Machine Learning / AI Engineering, ideally including technical leadership or consulting responsibilities.
• Proven experience designing and reviewing production AI/ML systems.
• Strong practical experience with modern LLM applications and Agentic AI systems.
• Deep understanding of:
  • LLM Agents and agentic workflows
  • Prompt Engineering
  • Function / Tool Calling
  • Structured Outputs
  • Context management
  • Hallucination mitigation
  • Guardrails and validation
  • Retry and fallback strategies
• Strong understanding of ML/LLM evaluation methodologies and how to measure AI system quality in production.
• Experience with AI observability, tracing, testing, and monitoring.
• Strong Python and SQL knowledge with the ability to review implementation and architecture decisions.
• Understanding of statistics, anomaly detection, forecasting, and data-driven system evaluation.
• Experience identifying technical risks, architectural weaknesses, and performance bottlenecks.
• Ability to translate complex technical findings into clear, practical recommendations for an engineering team.
• Strong communication and mentoring skills.
• English sufficient for technical discussions, documentation, and regular communication with the team.
   

Nice to Have

• Previous experience as a Lead ML Engineer, ML Architect, AI Architect, Staff/Principal ML Engineer, or ML Consultant.
• Experience with LangChain, LangGraph, or other Agent frameworks.
• Experience with AWS Bedrock, Claude, or other managed LLM platforms.
• Experience with FinOps, cloud billing, or cloud cost optimization.
• Knowledge of:
  • AWS CUR
  • AWS Cost Explorer
• Experience with Langfuse, LangSmith, RAGAS, or similar AI observability and evaluation platforms.
• Experience designing evaluation pipelines and golden datasets for LLM applications.
• Experience with forecasting and time-series analysis.
• Experience processing large financial or billing datasets.
• Understanding of multi-tenant architectures and secure AI tool execution.
• Experience optimizing LLM latency, token usage, and operational costs.
   

Technology Stack

• Python 3.12
• FastAPI
• LangChain
• LangGraph
• AWS Bedrock
• PostgreSQL
• SQL
• Langfuse
• RAGAS
• Docker
• Next.js / TypeScript
   

Engagement Format

• Part-time consulting engagement
• Flexible involvement based on project and team needs
• Regular technical reviews and consultations with the AI/ML team
• Architecture and solution reviews for key AI/ML initiatives
• Focus on technical guidance, quality assurance, process improvement, and mentoring rather than day-to-day feature implementation
   

Why Join Us?

• Influence the technical direction of a real production AI product without committing to a full-time role.
• Work on challenging problems at the intersection of Generative AI, Agentic AI, Cloud, and FinOps.
• Help shape the architecture and engineering practices behind production-grade AI systems.
• Work with a team that values measurable AI quality, reliability, security, and business impact.
• Apply your senior-level expertise where it has the highest impact: technical decisions, architecture, evaluation, optimization, and team development.
• Stay close to modern AI technologies while working in a flexible consulting format.

Job Summary
As a Software Engineer, you will work directly with AI coding models to evaluate their performance, identify weaknesses, debug incorrect outputs, and create stronger alternative solutions. This role is ideal for developers who enjoy problem-solving, code analysis, and improving how AI understands and generates technical answers.

Key Responsibilities

• Work with Frontier Labs, producing training data to train Al models. 
• Test and evaluate agentic coding models designed to perform complex engineering tasks at a senior developer level.
• Focus on creative problem-finding rather than traditional feature shipping. 
• Ideal candidates use AI, enjoy problem-solving, and like "outsmarting" Al systems. 

Requirements

• 3–4 years of hands-on experience as a Full Stack Developer on commercial projects, including B2B SaaS systems and data-heavy applications.
• Use AI tools (AI agents, Claude Code, Cursor, Codex or similar) in daily workflow.  
• Strong judgment across the full software lifecycle:
  • Reading a PRD and breaking it into Jira tickets
  • Estimating effort and scoping work
  • Architecture and design choices
  • Reviewing PRs
  • Debugging and recovering when blocked
• Strong proficiency with React.js and Node.js, with experience using Express.js or NestJS to build scalable backend systems that support complex business logic.
• Experience designing and integrating REST APIs. 

• Upper-Intermediate English (B2). 

   

Bonus:

• Computer Science or related education. 
• Python programming experience. 
• Strong understanding of algorithms and data structures. 

You will be part of building better AI systems by helping improve the quality, accuracy, and reliability of the answers they provide. If you want to use your engineering skills in a fast-growing AI field, this role is a strong opportunity to contribute to the future of AI-assisted development.

Middle QA Engineer

We’re looking for an experienced and proactive Middle QA Engineer to join our QA team at ODDITY and take ownership of quality across complex global e-commerce products.

This role is for someone who can work independently, communicate confidently with international teams, identify risks early, and contribute not only to testing features but also to improving the way the team approaches quality.

About ODDITY 🚀

ODDITY is a consumer-tech company transforming the beauty and wellness industry through technology, data, AI, and a highly customized e-commerce platform.

You’ll work with complex customer journeys, checkout and payment logic, promotions, third-party integrations, customer accounts, and high-impact features used by real customers worldwide.

Learn more about ODDITY: https://oddity.com

What We’re Looking For 🔎

• At least 2 years of practical experience in manual QA
• Strong English communication skills — you’ll collaborate with international teams daily
• Excellent communication, collaboration, and problem-solving skills
• Ability to work independently and take ownership of feature quality
• Strong understanding of testing methodologies and test design techniques
• Hands-on experience with functional, exploratory, integration, and regression testing
• Experience creating and maintaining test cases, checklists, and other QA documentation
• Strong knowledge of web applications and client-server architecture
• Confident use of Chrome DevTools, including Network and Console
• Practical API testing experience with Postman or similar tools
• Working knowledge of SQL
• Experience with Jira, Confluence, or similar tools
• Ability to analyze requirements, identify gaps, and communicate risks before development
• Practical experience using modern AI tools to improve the quality and efficiency of your work

We value people who communicate clearly, think critically, challenge assumptions respectfully, and focus on solutions rather than simply following instructions.

Working With AI 🤖

This is not a position focused on testing AI.

We expect AI to be part of your everyday workflow. You should be comfortable using tools such as ChatGPT, Claude, Gemini, Perplexity, or similar to:

• Analyze requirements and uncover gaps
• Generate test scenarios, edge cases, and risk areas
• Improve test documentation and bug reports
• Support technical investigations
• Structure and summarize complex information
• Review your own work and challenge your assumptions
• Automate or accelerate repetitive QA routines
• Learn unfamiliar concepts and tools faster

You should also be able to validate AI-generated output rather than accepting it blindly.

AI should amplify your expertise and critical thinking — not replace them.

What You’ll Do 🛠️

• Take ownership of quality for features from requirements through release
• Review requirements and identify risks, gaps, and unclear scenarios
• Plan and execute functional, exploratory, integration, and regression testing
• Test complex customer journeys, including checkout, payments, promotions, and user accounts
• Validate frontend, backend, API, and third-party integration behavior
• Create clear, actionable bug reports and maintain relevant QA documentation
• Investigate issues using DevTools, API tools, SQL, logs, and other available data
• Work closely with developers, product managers, designers, and other QA engineers
• Communicate quality risks clearly and help the team make informed release decisions
• Improve test coverage, QA processes, and team practices
• Support Junior QA Engineers through knowledge sharing and constructive feedback
• Use AI tools thoughtfully to make QA work faster, deeper, and more effective

Nice to Have ✨

• Experience testing e-commerce products
• Experience with checkout, payment systems, promotions, subscriptions, or customer accounts
• Knowledge of Magento, Shopify, or similar platforms
• Experience with mobile web and cross-browser testing
• Basic knowledge of Git
• Experience with test automation or the ability to read automated tests
• Familiarity with analytics and tracking validation
• Experience working with distributed international teams

What We Offer 💼

• Ownership of meaningful product areas
• Work on technically complex global e-commerce products
• A collaborative environment where QA has a real voice
• Opportunities for professional growth and broader responsibility
• Direct collaboration with experienced international teams
• Competitive compensation based on your experience and skills
• Remote work or an office in Kyiv
• Paid vacation and sick leave
• Medical insurance
• Sports compensation
• English lessons

We’re looking for a QA engineer who combines strong technical skills with ownership, clear communication, curiosity, and sound judgment.

If you want to influence product quality rather than simply execute test cases, let’s talk.