Jobs AI

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

About the role

We are looking for an experienced AI Solution Architect to join our CEE IT Digital Solutions team and lead the design of enterprise-grade AI solutions across the Microsoft ecosystem.

In this role, you will define architecture standards, shape technology decisions, and help delivery teams build scalable, secure, and cost-efficient AI solutions. You will work across the full AI landscape, from low-code experiences in Microsoft Copilot Studio to enterprise AI applications powered by Azure OpenAI, Microsoft Foundry, and modern agent frameworks.

This position is ideal for a hands-on architect who enjoys combining strategic thinking with technical execution and can confidently guide AI initiatives from concept through production deployment.

Your Responsibilities:

• Design and architect enterprise AI solutions, including RAG applications, AI agents, voice solutions, and intelligent automation initiatives.
• Define solution architecture standards, reusable patterns, and engineering best practices for AI projects.
• Drive architecture decisions across Microsoft Copilot Studio, Microsoft Foundry, Azure OpenAI, and related technologies.
• Support rapid prototyping, MVP development, and production-scale AI deployments.
• Design agentic workflows, multi-agent architectures, orchestration patterns, and Human-in-the-Loop solutions.
• Collaborate with developers, business analysts, project managers, security teams, and business stakeholders.
• Establish approaches for AI quality assurance, evaluation, monitoring, and performance measurement.
• Ensure compliance with enterprise governance, security, risk, and Responsible AI principles.

• Evaluate emerging AI technologies and recommend their adoption within the PwC environment.

   

What We Are Looking For:

• 8+ years of experience in software engineering, solution architecture, or enterprise application development.
• 4+ years of experience delivering AI, Generative AI, machine learning, or intelligent automation solutions.
• Strong experience with: Microsoft Copilot Studio, Azure OpenAI, Azure AI Search, Azure cloud services and architecture,Python.
• Experience with SQL, relational databases, and REST APIs.
• Strong understanding of: LLMs and Generative AI, RAG architectures, embeddings and vector search.
• LangChain and/or LangGraph, Agentic AI and multi-agent architectures.
• AI evaluation frameworks and quality metrics.
• Experience working with GitHub and modern source control practices.
• Fluent English (written and spoken).

Nice to have
Power Platform (Power Automate)
Azure DevOps and CI/CD practices
Microsoft Graph API
Agent frameworks such as Microsoft Agent Framework 

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for a Senior AI Platform Engineer to build and scale the infrastructure behind production AI agents.

Our AI agents conduct live conversations — including training role-plays, outbound calls, and interviews — and turn conversations into scores, summaries, and coaching insights.

What you'll work on

• AI Agents: Build and run production voice/conversational agents, including state, interruptions, latency, configuration, versioning, and testing.
• Durable Workflows: Design event-driven pipelines using queues, webhooks, retries, and idempotent processing.
• LLM Pipelines: Build multi-step analysis pipelines using frontier and open-source models, balancing quality, latency, and cost.
• Evals & Observability: Build tracing, evaluations, and quality gates for agents, prompts, and models.
• Architecture & Data: Own technical decisions and design secure multi-tenant systems using PostgreSQL.

• Engineering: Review code, write design notes, improve architecture, and help other engineers grow.

   

What we're looking for

• Production experience building and operating AI agents with real users.
• Experience with voice agent platforms or open-source agent frameworks.
• Strong understanding of latency, interruptions, state, and production failure modes.
• Production experience with durable workflows and event-driven systems.
• Hands-on experience with retries, queues, webhooks, and idempotency.
• Experience shipping LLM-powered features with frontier or open-source models.
• Experience with LLM observability, tracing, and evals.
• Strong PostgreSQL skills, including schema design and migrations.
• Strong TypeScript and comfortable with Python.
• Strong written English and solid technical communication.

Nice to have

• Speech/transcript pipelines at scale.
• Speaker diarization and long-form audio processing.
• Open-source voice agent frameworks.
• SIP, telephony, phone carriers, or WebRTC.
• Building eval sets that gate prompt/model changes.
• Next.js and Supabase.
• Open-source contributions to AI, voice, or LLM tooling.

How we work

• AI-assisted coding is expected — we care about your ability to verify and judge AI-generated code.
• Written-first: design notes, clear PRs, and async communication.
• PR + CI for every change.
• Staging before production.
• Regular code reviews and pairing.
• Small team, high ownership, direct impact on architecture and product.

Why join

You'll own a meaningful part of the production AI stack, from live voice interaction to durable processing, LLM analysis, evaluation, and the final product experience.

If you match most of the requirements but not all of them, apply anyway.

Ajax Systems, an international tech company and the largest manufacturer of security systems in Europe.We are looking for a new team member to join our Video Devices Division as a Computer Vision Engineer .

The Video Devices Division is responsible for the full development cycle of Ajax video devices, covering every stage from initial concept creation to mass production launch and further scaling. The team focuses on building complex products that combine mechanical design, hardware development, and the integration of low-level software to ensure stable real-time system performance.The development process involves deep expertise in optics, image quality, embedded systems, Wi-Fi and networking technologies, as well as audio tuning. The division ensures full vertical integration of all device components, creating technologically complete solutions that meet the reliability standards of the Ajax ecosystem and the requirements of global industrial production.

What you’ll work with:

• object detection;
• object tracking;
• face recognition;
• multi-modal search;
• acoustic intelligence;
• models optimization for edge inference;

• research and deliver sota computer vision solutions to exceed today’s cctv domain expectations.

   

Your cross-functional partners:

• ML team;
• platform team;
• annotation team;

• QA team.

   

What we’re looking for:

• 5+ years with machine learning;
• 2+ years with computer vision and python;

• experience with pytorch.

   

Nice to have:

• experience with C++;
• deploy AI models on edge devices;

• computer vision analytics troubleshooting.

   

We offer:

• the opportunity to suggest and implement your own ideas that directly influence the product and its mass production;
• a place in a fast-growing company with a motivated and professional team;
• competitive salary;
• medical insurance;
• corporate English classes;
• the opportunity to participate in Ajax’s internal beta-testing program for security systems;
• discounts from partner companies;
• discounts on Ajax products.

Ajax Systems is a Ukrainian success story that has grown into a global product. Ajax devices are trusted by more than 4.5 million end users and 330,000 PRO users in over 180 countries. The company provides comprehensive solutions to protect residential and commercial properties of all sizes. Today, Ajax portfolio includes 280 devices for intrusion protection, video surveillance, fire safety, and comfort and automation.

We’re looking for a mid-level Business Analyst to help design custom business systems and automate processes, using AI coding agents to prototype and build solutions
 

Responsibilities

• Analyze business processes and identify opportunities for improvement and automation
• Gather requirements and translate them into workflows, concepts and tasks
• Build solutions using AI coding agents
• Work with clients, stakeholders and developers to deliver solutions that meet business needs
   

Requirements

• Experience in business analysis and solution design
• 6+ months of hands-on agentic coding experience with tools such as Claude Code, Codex, or Cursor
• Understanding of APIs, integrations, and the software development lifecycle
• Strong analytical and communication skills
• English B2 or above

We’re looking for a Senior Azure Platform / AI Engineer for a long-term engagement with an enterprise client. You’ll work directly with the client’s IT and Security teams in a sprint-based model.

What you’ll do:

• Design and maintain Azure infrastructure: AKS, Entra ID, Private Endpoints, VNets, Network Security Perimeters, multi-region
• Deploy and operate AI/ML workloads: Azure OpenAI, AI Foundry, RAG, multi-agent systems, vLLM, embedding pipelines
• Own IaC & CI/CD: Terraform, GitHub Actions, OIDC federation, Helm/Kustomize, secret management
• Data integrations: Microsoft Fabric, PostgreSQL, Python ETL, Power BI API
• Backend/frontend support: Python/FastAPI (async), React + TypeScript (Vite)

Stack:
Azure AKS Entra ID RBAC Key Vault APIM AI Search Azure OpenAI AI Foundry Azure ML Terraform GitHub Actions Helm Microsoft Fabric PostgreSQL FastAPI React TypeScript

Requirements:

• 5+ years of Azure platform engineering
• Strong communication with enterprise clients (English)
• Experience working with IT/Security stakeholders

Nice to have:

• Production AKS & Azure ML model serving
• Azure OpenAI in production
• Locked-down / regulated Azure tenants
• FDE or embedded team experience

Format: Remote, Europe, long-term , sprint model, start ASAP.

What AppRecode offers

• 20 days of paid annual leave plus public holidays.
• 5 paid sick days per year.
• Remote-first work environment.
• Friendly and supportive team culture.
• Personal development plans and access to experienced mentors and technical leaders.
• Reimbursement for sports activities and professional certifications (after probation).
• Ongoing learning opportunities: internal trainings and knowledge-sharing sessions.
• Free English classes if you want to further improve your communication skills.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv — you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.
•  

We are looking for a Senior Python Developer with strong experience in data processing, AI-related development, and modern DevOps practices.

Main Responsibilities:

• Design, develop, and maintain Python-based services, data pipelines, and tools;
• Work with large datasets using Pandas, NumPy, and related libraries;
• Contribute to AI/ML-related features (data preparation, model integration, basic experimentation);
• Collaborate with DevOps to containerize and deploy applications (Docker, CI/CD);
• Write clean, testable, and well-documented code;
• Participate in code reviews.

Key Requirements:

• 5+ years of professional Python development experience;
• Strong understanding of core CS concepts: data structures, algorithms, complexity;
• Experience with document processing and data extraction from PDFs using tools such as PyPDF2, pdfminer, tabula-py, or similar libraries;
• Solid experience with data processing in Python:
  • Pandas (DataFrames, joins/merge, groupby, aggregations, time series, data cleaning);
  • NumPy (array operations, vectorization, basic numerical computing);
• Experience with Python in AI/ML contexts:
  • Working with ML/AI libraries (e.g., scikit-learn, TensorFlow, PyTorch) is a strong plus;
  • Experience in data preparation, feature engineering, and integrating models into applications is an advantage;
• DevOps / infrastructure:
  • Experience with Docker (building and running containers);
  • Familiarity with CI/CD tools (GitHub Actions, GitLab CI, Jenkins, etc.);
  • Experience with at least one cloud platform (AWS, GCP, or Azure);
• Strong Git skills (branching, pull requests, code reviews);
• Experience with testing frameworks (e.g., pytest)
• Written and spoken English at B2 level.

Policy statements:
www.pwc.com/ua/uk/about/privacy.html

OTAKOYI is looking for a smart and eager Senior AI Engineer to join our project team. We like challenges and self-development. If you like it too, don’t hesitate, join us!

Our Partner has an advanced, enterprise-grade agentic AI platform that centralizes intelligence, knowledge, and task automation across ecosystem. Built to enhance productivity, orchestrate complex workflows, and provide proactive insights, it is more than a chatbot—it’s an AI-powered front-end for the company's digital transformation. The platform also underpins another application known as Studio AI, for which this role will also be responsible.

This is a pivotal role, responsible for defining and executing the long-term AI strategy, owning system architecture, and providing strong technical direction to evolve the platform. If you have a passion for building transformative AI solutions, excel in strategic thinking, and thrive in taking architectural ownership — this role offers the opportunity to make a lasting impact.
The ideal candidate will bring a unique mix of visionary thinking, deep technical expertise, and hands-on experience, capable of driving Navigator and Studio AI’s next phase of innovation through technical leadership and architectural excellence.
 

Required Skills 

• Deep AI Expertise: Deep knowledge of machine learning techniques, NLP, LLMs, and data-driven AI architectures, with hands-on experience designing and deploying complex AI systems;
• AI Tech Stack: Proficiency with AI development tools and frameworks such as Azure ML, PyTorch, TensorFlow, LangChain, and transformer-based models;
• Cloud Infrastructure: Advanced experience with Azure-based cloud ecosystems and Kubernetes-based orchestration for scalable AI workloads;
• Production-Grade AI Systems: Experience with vector search (e.g., Milvus), real-time APIs, embedded analytics, and third-party integrations (e.g., MS Graph API, Copilot Studio);
• System Design and Architecture: Expertise in designing scalable, secure, and fault-tolerant AI systems, including familiarity with microservices, API management, and real-time data processing;
• Technical Communication: Ability to clearly articulate architectural decisions, technical trade-offs, and AI roadmaps to cross-functional stakeholders;
• Strategic Mindset: Strong analytical and strategic thinking skills, with the foresight to anticipate future AI trends and an understanding of how to apply them to a multi-functional platform like Navigator;
• Upper-Intermediate level of English is mandatory.

Preferred Skills 

• Industry Experience: Experience within a large, matrixed organization,
preferably in technology or a related industry;
• Experience with AI-driven Multi-Modal Systems: Knowledge of systems integrating chat, voice, visual data, and embedded dashboards is a plus;
• Enterprise AI Context: Familiarity with compliance, governance, and scalability considerations in deploying AI in enterprise environments;
• Project Management: Experience with prioritization and execution in agile settings (without direct team ownership).

Responsibilities 

• Vision & Strategy: Develop and continuously refine the long-term vision , driving innovation, user-centricity, and strategic alignment with Company's broader business goals;
• AI & System Architecture: Lead the design and development of AI-driven architecture, ensuring scalability, robustness, and cutting-edge technology integration across ML, NLP, data pipelines, and automation components;
• Cross-Functional Collaboration: Partner closely with stakeholders from product, design, engineering, and business units to ensure Navigator’s roadmap aligns with business needs and delivers tangible value across Company;
• Platform Innovation: Keep Navigator at the forefront of technology by
incorporating emerging trends in agentic AI, multi-modal interfaces, generative AI, and autonomous orchestration;
• Quality & Performance Optimization: Establish benchmarks for platform performance, reliability, and security. Regularly review and refine Navigator’s core systems to ensure peak performance and user satisfaction;
• User Experience Focus: Drive a user-first approach, ensuring that Navigator’s functionality and interface support intuitive and seamless interactions for Company's employees, partners, and customers;
• Vendor & Technology Management: Evaluate and manage strategic relationships with third-party vendors, especially in areas like NLP, Microsoft integrations (e.g., Copilot), and cloud infrastructure (Azure), to leverage the best available technology.

Recruitment process 

1. Pre-screening Interview with Recruiter (up to 45 minutes)
2. Tech Interview (up to 1,5 hour)
3. Client Interview (up to 45 minutes)

Our Customer:

Our customer develops AI-powered voice and SaaS solutions that connect intelligent bots and agents with communication platforms. The engineering environment combines modern test automation technologies with AI-assisted development practices across cloud-based and on-premises solutions.

Your Tasks:

• Design, develop, and maintain automated tests using Python and Pytest.
• Incorporate AI-assisted development tools into daily testing and engineering activities.
• Design and apply AI-driven workflows and agents to support test development, analysis, troubleshooting, and automation.
• Collaborate with developers and other R&D team members throughout the software development lifecycle.
• Build and maintain test automation infrastructure and frameworks.
• Perform manual testing when required and identify areas where testing can be effectively automated.
• Investigate test failures, analyze logs and system behavior, and distinguish between product-related and automation-related issues.
• Contribute to improving the reliability and effectiveness of automated testing processes.

Required Experience and Skills:

• 3+ years of experience in QA Automation or Software Automation.
• Strong programming skills with hands-on experience in Python.
• Hands-on experience with AI-assisted development tools.
• Practical experience using AI as part of software development or testing workflows, including AI agents, AI-driven workflows, code generation, analysis, and automation.
• Ability to work effectively with AI tools through prompting, context management, validation of generated output, and iterative workflows.
• Hands-on experience with Pytest and automated testing frameworks.
• Experience with UI and/or API test automation.
• Experience with Git and Linux.
• Experience with Docker.
• Experience with cloud technologies; Azure is preferred.
• Strong debugging, troubleshooting, and research skills.
• Ability to understand complex systems and translate requirements into effective automated test coverage.
• Ability to learn independently and adopt new technologies.
• Good written and verbal communication skills.
• Fluent English.

Would Be a Plus:

• Experience with Playwright.
• Knowledge of LLMs and AI agents.
• Experience with Voice Bots.
• Experience with CI/CD pipelines.
• Kubernetes.
• Microservices architectures.
• SIP/VoIP.
• SaaS platforms.
• Experience testing AI-powered applications.

About the Role

Our client runs a leading browser-based video platform for live streaming, conferences, webinars, and training, supporting thousands of simultaneous viewers. We’re looking for a Senior / AI-Native QA Lead to own QA strategy across the product lifecycle, raise quality standards, mature QA processes, and introduce modern AI-driven testing practices. You’ll work closely with Product, Engineering, and Design, combining hands-on testing with strategic ownership and helping shape how quality is built into the product.
Responsibilities

• Define and evolve QA strategy across the product lifecycle
• Develop and maintain test plans, cases, and scenarios
• Lead functional, regression, exploratory, and integration testing
• Own the defect lifecycle and quality of bug reporting
• Partner with Product, Engineering, and Design on requirements and acceptance criteria
• Integrate AI tools and agent-driven approaches into QA workflows to improve efficiency, coverage, and feedback loops
• Define and track QA metrics and quality indicators
• Mentor and support junior and mid-level QA engineers 

Requirements

• 6+ years of QA experience with a strong track record of delivering high-quality software
• Strong manual, exploratory, and risk-based testing skills
• Experience developing and implementing QA strategy at a team or product level
• Practical experience applying AI to QA, with examples you can walk us through: the problem, your approach, how you validated the results, and what changed as a result
• Understanding of AI limitations such as hallucinations, inconsistency, and unreliable outputs, with practical approaches to validating AI-generated results
• Experience with defect tracking and test management tools such as Jira, TestRail, or Zephyr
• Exposure to CI/CD and cloud environments; AWS is a plus
• Experience testing web and mobile applications across browsers and platforms
• Solid understanding of SDLC and Agile/Scrum practices
• English: Upper-Intermediate (B2+) or higher 

What We Offer

• A collaborative, multinational Agile team building a high-scale platform, with real ownership of QA strategy and the opportunity to introduce AI-enabled testing practices
• Hybrid work format, combining remote work with time in our Lviv office
• Daily interaction with native English speakers, providing natural opportunities to use and improve your English
• 18 working days of paid vacation, 10 working days of sick leave, and 11 paid Ukrainian statutory holidays
  
   

About the Company

Our client is a financial technology services provider dedicated to expanding global access to digital assets by building innovative solutions in the cryptocurrency ecosystem. Their products provide exchanges, liquidity solutions, prediction markets, and enterprise-grade white-label integrations for institutional clients worldwide.

We are looking for an exceptional, cutting-edge AI-Native Product Manager to own our core Institutional Trading & Derivatives product suite. This is an elite technical product role where deep financial domain mastery meets absolute state-of-the-art AI orchestration.

Key Pillars of Success

To excel in this role, you must bring a battle-tested foundation across three non-negotiable pillars:

1. Cutting-Edge AI-Native Execution: You don't just use ChatGPT or Claude for PRDs and prototyping. You operate with autonomous agents, MCP (Model Context Protocol) integrations, browser/computer use, and human-in-the-loop review loops to dramatically multiply your operational throughput.
2. Deep Trading & Derivatives Mastery: You possess a deep, structural understanding of institutional market mechanics, order lifecycles, margin systems, liquidation engines, funding rates, oracles, exposure, and hedging.
3. End-to-End Ownership & Measurable Impact: Your ownership doesn't end at handing docs to devs or launching on staging. You own the full lifecycle—from discovery, build, and QA to client rollout, adoption, and iteration—backed by self-derived, quantified metrics (e.g., SQL-verified impact).

What You'll Do

• Product Ownership: Take complete end-to-end ownership of our white-label institutional trading, derivatives, and risk management infrastructure.
• Agentic Workflow Integration: Leverage autonomous AI agents and MCP servers to automate complex product research, spec generation, QA verification, and client delivery workflows.
• Institutional Client Rollout: Partner directly with institutional clients and B2B partners to deeply understand their trading workflows, capture complex requirements, and drive product adoption.
• End-to-End Execution: Drive features through the complete lifecycle: discovery, system spec definition, hands-on engineering alignment, QA validation, launch, and post-launch analytics.
• Data & Impact Analytics: Autonomously query databases (SQL) and analytics tools to track, measure, and optimize real client usage and performance metrics post-launch.
• Engineering & Business Alignment: Challenge technical and business assumptions constructively, maintaining direct, transparent communication across cross-functional engineering teams.

AI-Native Expectations

We are looking for candidates who operate at or above the absolute cutting edge of AI tooling:

• Agentic Workflows: Hands-on experience building or utilizing MCP (Model Context Protocol) integrations, autonomous loops, or computer/browser-use agents.
• Execution & Leverage: Using AI as a force multiplier across all product phases—from automated code/spec reviews and workflow automation to deep data processing and client communication.
• Technical Integrity: Using AI to elevate your productivity without substituting AI output for genuine domain expertise or critical engineering judgment.

Who You Are

• Autonomous & Proactive: Capable of taking a broad product domain and generating tangible, visible value within your first 90 days without step-by-step guidance.
• Transparent & Honest: Grounded in high integrity, objective self-awareness, and clear communication. You know your strengths, acknowledge knowledge gaps directly, and never bluff technical answers.
• Systems Thinker: Comfortable reasoning about APIs, data flows, state machines, edge cases, and complex risk models alongside senior engineers.

Qualifications

• English: Upper-Intermediate to Advanced (both written and verbal) for high-stakes institutional communication.
• Experience: 4+ years of software product management experience, specifically within fintech, crypto trading platforms, or institutional finance.
• Domain Expertise: Proven hands-on experience with institutional trading infrastructure, derivatives (perpetuals, futures, options), risk mechanics, margin, and liquidity.
• B2B / Client-Facing Delivery: Demonstrated track record of launching white-label or enterprise B2B products directly for external institutional clients.
• AI-Native Mastery: Practical, advanced usage of modern agentic AI tools and environments (MCP, Cursor, Claude Code, autonomous loops).
• Data Competency: Solid experience writing SQL queries independently to measure feature performance, user funnels, and adoption metrics.

Bonus Points:

• Software development or engineering background.
• Direct experience running or supporting a trading desk, market-making operations, or liquidity adapters.
• Deep knowledge of crypto-native derivatives protocols, Web3 infrastructure, or prediction markets.

We Offer

• Flexibility & Hubs: Flexible working hours with physical office access in Ukraine and Poland (Wroclaw).
• Health & Wellness: Medical Insurance in Ukraine and Multisport program in Poland.
• Time Off: Paid vacation, sick leaves, and observance of official holidays.
• Growth & Support: Corporate English classes up to three times a week, plus mentoring and educational budgets.
• Contractor Support: Complete tax and accounting services provided for Ukrainian contractors.
• Equipment: High-end hardware and development equipment provided by the company.
• Culture: Regular corporate activities (team buildings, tech talks, parties) combined with an advanced bonus system.

Our client builds an enterprise LLM gateway. It connects customers’ applications and AI agents to multiple model providers through an OpenAI-compatible API. Customers register their own provider API keys. The gateway routes requests, reduces model costs, enforces policies, and tracks cost and usage per agent.

We are looking for a Senior Full-Stack Engineer with strong Python and TypeScript skills. You will build production SaaS features across the backend and frontend. Your work will cover database design, FastAPI endpoints, React screens, tests, and deployment. Features can also include Python middleware in the gateway.

Two areas will be your primary focus:

1. Payments and billing — building the commercial layer on top of the platform’s usage metering:subscription plans, usage-based billing, invoicing, credits, and entitlement enforcement.
2. Gateway guardrails and telemetry — building the policy enforcement and observability layer that makes the gateway safe, measurable, and auditable for enterprise customers.

You will join a small, senior, distributed team. You will own features through deployment and take part in architecture decisions. When needed, you will work directly with customers to define, build, deploy, and improve features that use AI.

What’s interesting about this project:

• Own features from database design to the customer interface and production deployment.
• Work with Python, FastAPI, React, TypeScript, Kubernetes, and Terraform.
• Help decide how the product works and how the team builds it.
• Build a gateway that connects customer applications and AI agents to multiple model providers.
• Measure how gateway changes affect model costs, response quality, and latency.

What you’ll work on

• Payment system integration (primary focus): Design and build the billing layer end to end — integrate Stripe (or an equivalent provider) for subscription plans, metered/usage-based charging, invoicing, credits and prepaid balances, and payment lifecycle handling.
• LLM gateway guardrails (primary focus): Design and implement the policy layer that inspects traffic flowing through the gateway.
• Telemetry and observability (primary focus): Extend the request telemetry pipeline that powers customer-facing analytics — enriching per-request records with cost, token, cache, routing, and guardrail metadata, building efficient time-series aggregations.
• Gateway middleware: Build Python hooks inside the LLM proxy. Work includes prompt compaction, model routing based on request complexity, semantic caching, and response enrichment. Keep request handling correct and latency low.
• Backend API development: Build and evolve FastAPI services with async SQLAlchemy and PostgreSQL, including multi-tenant data isolation, RBAC, session-based authentication, encrypted secret storage, and Alembic migrations.
• Frontend development: Build customer-facing features in React and TypeScript — billing and plan management, guardrail configuration, telemetry and spend analytics views, admin/provisioning screens, and the LLM playground with streamed responses.
• Multi-provider model management: Extend provider integrations, model catalogues, budgets, and rate limits so tenants can bring their own models and providers safely.

Technology Stack

• Backend: Python 3.13, FastAPI, Uvicorn, Pydantic, Poetry
• Data: PostgreSQL 16, SQLAlchemy 2 (async, asyncpg), Redis Stack
• LLM Gateway: OpenAI-compatible proxy (LiteLLM) with custom Python middleware, multi-provider model routing
• Frontend: React, TypeScript, Vite, Tailwind CSS, Chart.js
• Payments: Stripe or equivalent — subscriptions, metered billing, webhooks, invoicing
• Testing: pytest, Vitest, Testing Library
• Infrastructure: Google Cloud Platform, Kubernetes (GKE), Helm, Terraform, Docker
• CI/CD: GitHub Actions
• Observability: Prometheus, Grafana, distributed tracing
• Code quality: black, isort, flake8, ESLint, Prettier

Responsibilities

• Own features end to end across the gateway middleware, backend API, and frontend — including schema design, API contracts, UI, tests, and rollout.
• Build and operate the subscription and usage-based billing system, including payment provider integration, webhook reliability, usage-to-invoice mapping, and entitlement enforcement.
• Design and implement guardrails that inspect and enforce policy on LLM prompts and completions, with per-tenant configuration and full auditability.
• Extend the telemetry pipeline and analytics aggregations that power customer-facing cost and usage reporting, and add tracing, metrics, and alerting across services.
• Write middleware that runs in the live request path, treating latency, failure modes, and graceful degradation as first-class design concerns.
• Design multi-tenant data models with correct isolation between organizations, workspaces, and keys.
• Write meaningful automated tests for the code you ship.
• Participate in architecture decisions, code reviews, and planning; document decisions for a distributed team.
• Handle sensitive data responsibly — secret encryption at rest, least-privilege access, and audit logging.

Requirements

• 5+ years of professional full-stack experience. You have built and shipped production SaaS features across the backend and frontend.
• Strong Python skills and experience building production APIs with FastAPI (or Django REST / Flask, with a willingness to work in FastAPI), including async programming
• Strong React and TypeScript skills — comfortable with component-driven UI, SPA state management, routing, and integrating REST APIs including streamed responses
• Practical familiarity with LLM integrations, retrieval-augmented generation (RAG), AI agents, or AI tools such as Cursor, Claude Code, or Copilot. You do not need an AI research or specialist agent infrastructure background.
• Experience with Stripe or a similar payment provider. Relevant work includes subscriptions, webhooks, idempotency, proration, refunds, and usage-based billing in production.
• Solid PostgreSQL skills: schema design, migrations, indexing, and query optimization — including aggregations over large event/log tables
• Experience with multi-tenant architectures, authentication and authorization, and tenant data isolation
• You can use Docker and run services in Kubernetes. You can read a Helm chart and debug a failing pod.
• Experience with Redis or a comparable cache, and with designing for cache correctness and invalidation
• You work well in a startup with limited structure. You clarify unclear problems, choose practical solutions, and deliver them with little oversight.
• Clear written and spoken English for collaboration and documentation

Nice to Have

• Experience working directly with customers to define, build, and improve solutions.
• Experience with LLM API streaming, token accounting, rate limits, retries, and cost tracking.
• Experience building guardrails, content moderation systems — or working on trust & safety, compliance, or security tooling
• Familiarity with LLM gateways or proxies or with building an internal LLM platform
• Experience with LLM observability and evaluation tooling and with building evaluation harnesses
• Experience with usage metering and rating systems — turning high-volume event streams into accurate, auditable billable quantities
• FinOps or cloud-cost-optimization background; experience showing customers where their money goes
• Terraform and infrastructure-as-code experience on GCP (GKE, Cloud SQL, Secret Manager) or an equivalent cloud

Our benefits:

• No micromanagement
• Freedom to engage in decision-making and implementation
• Ability to work in a team of professionals (the ratio of middle and above specialists 80/20)
• Participation in the development of high-quality products
• Direct communication with clients on a partnership level
• Health insurance
• A $1,000 flexible benefits budget per individual year
• 20 paid working days off and 10 days sick leave
• Opportunity to work remotely

Join us and be among those who care!

About Altus Nova
Altus Nova combines strategy consulting, product management, and software development into a single service. We work closely with client executives and front-line teams to understand business processes, define practical solutions, and deliver value through phased roadmaps. Our work spans healthcare, financial services, ecommerce, logistics, and infrastructure. We remain accountable for the systems we build and often operate and support them after delivery.

The role
You will design, build, and evolve cloud-native back-end systems, using AI to accelerate disciplined engineering. You will independently apply agreed architectural and engineering practices, work directly with clients and teammates to clarify requirements, and own your work through validation and support. Strong engineering fundamentals and judgment are essential to directing AI effectively.

What you will do

• Analyze business workflows and requirements with clients and the product team. Surface contradictions, missing requirements, risks, and impractical assumptions before directing implementation.
• Develop technical designs, interface contracts, implementation plans, and acceptance criteria. Maintain shared specifications and decision records as requirements and solutions evolve.
• Design and build modular back-end capabilities and integrations with clear boundaries. Evaluate changes for compatibility, dependencies, security, performance, and supportability.
• Direct agentic development tools through bounded tasks and explicit instructions. Review generated changes and retain ownership of code quality and the overall solution.
• Deliver in small, testable iterations. Use focused research spikes to resolve technical uncertainty, and contribute to estimates and transparent delivery planning.

• Build automated validation and diagnostic capabilities. Work with QA and DevOps on release readiness, secure deployment, production support, and learning from incidents.

   

Required experience and engineering foundations
5+ years of professional back-end engineering experience. The 12-month AI experience requirement below is part of this total.

• Strong computer science and software engineering fundamentals, grounded in substantial hands-on back-end development with a production stack such as C#/.NET, Python, or Node.js/TypeScript.
• Hands-on production experience with at least one of AWS, Azure, or GCP, including serverless compute, messaging, data storage, identity, observability, and deployment.
• Sound understanding of API design, service and module boundaries, SQL and NoSQL data modeling, distributed systems, concurrency, and event-driven processing.
• Practical experience with automated testing, code review, source control, CI/CD, infrastructure as code, application security, and diagnosing production problems.

• Ability to read, critique, debug, and modify code and resolve technical issues independently of AI. You remain accountable for designs, implementations, and outcomes regardless of how they are produced.

   

Required experience with design time AI
Design-time AI means using AI during analysis, design, implementation, testing, and maintenance. We require practical proficiency in rigorous engineering across repeated changes to complex systems.

• At least 12 months of sustained professional AI-assisted software development within your overall engineering experience, including hands-on use of agentic coding tools such as Claude Code, Codex, or comparable tooling.
• Experience delivering production software with AI and maintaining it through multiple subsequent iterations. You can explain your specifications, architectural choices, change controls, validation, and lessons from failures. Vibe coding alone does not meet this requirement.
• Ability to apply disciplined, specification-driven development: clarify ambiguity with the appropriate owners, expose assumptions, define technical designs and acceptance criteria, and keep specifications, contracts, decisions, and implementation aligned.
• Effective delegation to AI: decompose work into bounded tasks, provide relevant context and constraints, anticipate misinterpretation, define acceptance criteria, and critically review outputs. Use adversarial review to challenge assumptions and surface gaps.
• Ability to discuss choosing models for analysis, implementation, and review based on capability, reliability, latency, and cost, and managing context and token consumption in development workflows.
• Understanding of how architectural boundaries, explicit interfaces, and contracts contain change. Explain how you would prevent or detect unintended rewrites, assess downstream effects, and maintain a complex application across iterations.
• Ability to discuss validation controls, their limitations, and when particular controls are mandatory or implementation choices. Recognize that AI-generated code and tests can share mistaken assumptions and explain how you would challenge them.

• Ability to describe how specific tools and workflows preserve shared project context and enable another engineer to continue the work. Willingness to learn and work with Altus Nova Assistant (ANA), Altus Team AI, and the AI technologies and frameworks we develop.

   

Required runtime AI understanding
Runtime AI means AI capabilities operating within deployed solutions. You must meaningfully discuss the concepts below and outline a basic production workflow. Practical runtime AI implementation experience is a strong advantage.

• Explain model limitations, context management, retrieval, structured outputs, tool use, and cloud-based agentic workflows, with the ability and commitment to mature into production implementation.
• Distinguish functionality best implemented with deterministic code from work suited to LLM reasoning. Discuss how the approaches can be combined within reliable systems.
• Discuss workload routing among models based on capability, reliability, latency, and cost. Explain context and token management and guardrails for budgets, retries, and agent execution limits.
• Discuss safeguards that reduce and detect hallucinations, including grounding, output validation, evaluation, and appropriate abstention or escalation when evidence is insufficient.
• Distinguish generating a recommendation from executing an action. Discuss least-privilege access, human review and approval, rejection paths, failure handling, observability, and recovery.

• Discuss protecting client information in development tools and runtime systems, including secrets management, prompt injection, untrusted retrieved content, and restrictions on agent access to tools and systems.

   

Communication and collaboration
- Strong spoken and written English is required. You must explain complex concepts in plain language, listen carefully, ask precise questions, and communicate effectively with client executives, subject-matter experts, and engineering teammates. Constructively challenge flawed specifications and work with their owners to resolve them.
- You must help teammates succeed, surface blockers early, and provide clear handoffs. Effective delegation to AI requires instructions others can understand and outputs you can explain and defend.
- You will work with Product Managers, Business Analysts, architects, designers, front-end engineers, QA, and DevOps. We value constructive debate, clear decisions, and helping teammates succeed. Engineers engage directly with clients, participate in planning and estimation, demonstrate their work, document decisions, and track time accurately. Production reliability is a shared priority.

Preferred experience

• C#/.NET development and experience adapting across back-end languages and frameworks.
• Production AI workflows, including model routing, retrieval, evaluations, human approval, and cost controls.

• Legacy modernization, third-party integrations, or business-critical systems in complex client environments.

   

How we assess candidates
Our process includes a collaborative, real-time whiteboard session where you analyze unfamiliar problems, clarify ambiguity, and explain your approach with the interviewers. Candidates who pass complete a practical task using AI and walk the team through the resulting specifications, implementation, and validation. You must demonstrate independent reasoning, understand the outputs, and be able to take responsibility for the outcome.

Codebridge is looking for an Applied AI Engineer to build the AI functionality of a corporate learning platform end to end. Agents — planning, tool use, acting across the product — are the core, surrounded by retrieval, content generation, and labs. Everything is model-agnostic across Claude, OpenAI, and Gemini. 

Responsibilities: 

• Design and ship agents — the core of the role: planning, tool use, memory, and guardrails, orchestrated with LangChain/LangGraph, exposed via MCP where it fits, running behind a provider-abstraction layer with model routing and cost control 
• Build product features end to end — from the front end through backend services to the model call in the cloud 
• Set up and tune retrieval: ingestion, chunking, retrieval quality, reranking, and grounded generation with citations 
• Evolve the content-generation pipeline: grounded generation from ingested sources, structured outputs that survive provider differences, and accuracy checks that keep generated material true to source 
• Develop hands-on lab environments in a sandboxed execution platform: mock APIs, auto-verification harnesses that grade learner work, and managed multi-provider model access with per-user budgets 
• Take charge of evaluation infrastructure: task datasets, deterministic and model-based graders, regression suites, and cross-provider benchmarks 

Requirements: 

• 4+ years in software engineering, with production systems you can walk through end to end 
• 1+ years shipping production LLM applications — agents, tool use, retrieval — with hands-on work across at least two of the three major platforms (Anthropic, OpenAI, Google) 
• Depth in agent development: tool use, memory, multi-step orchestration, and MCP — you've built and debugged MCP servers, not just consumed them 
• Claude Code as a daily working tool, plus working fluency with the OpenAI API and Gemini — or a demonstrated ability to get there fast, since the abstractions matter more than any single SDK 
• Evaluation fluency: task datasets, deterministic and model-based graders, regression suites. "I tested it manually and it looked fine" is an unfinished sentence 
• Solid Python for LLM tooling, with experience in LangChain/LangGraph or an equivalent orchestration framework 
• Comfort with sandboxed cloud execution environments, CI, and API security basics 
• Clear technical communication — you can review someone else's work rigorously and kindly, and explain a model limitation to a non-engineer without jargon 
• A responsible, outcomes-focused mindset 
• Advanced English or higher 

Nice to Have: 

• Experience with TypeScript/Node/React 
• Provider certifications (Anthropic, OpenAI, or Google Cloud AI) or demonstrable equivalent depth 
• Experience with learning platforms, developer education, or technical enablement 
• Experience with LLM gateway/routing layers, structured-output schemas across providers, or multi-model evaluation tooling 
• Public evidence of technical judgment: open-source contributions, technical writing, or talks 

We Offer: 

• Technical Ownership: You own the AI architecture and the standards behind it 
• Modern AI Work: Agents, retrieval and evaluation as the everyday job, not a side experiment 
• Collaborative Environment: A team that values partnership, creativity, and mutual respect 
• Flexible Work: Work remotely from the comfort of your home or join us in our modern Kyiv office 
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually 
• Professional Growth: Compensation for courses, certifications, and learning resources 
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Claude Code, GitHub Copilot, etc.) 

Recruitment Process:    

1. HR&Technical Interview 
2. Client stage 
3. Offer 

Project overview

Testing Solutions is focused on building and improving AI powered test automation capabilities for quality assurance processes. You will contribute to a practical automation environment using Playwright, Python, Apium and Copilot based workflows.

Position overview

It is an onsite position for Cyprus (relocation is required).
We are looking for a Python Developer with Playwright to support AI powered testing solutions in an onsite environment. You will help set up and improve AI automation solutions used in QA activities.

Technology stack

Playwright, Python, Apium, Copilot

Responsibilities

• Develop AI powered test automation solutions using Playwright, Python and Apium
• Set up AI automation solutions for QA workflows
• Collaborate in an onsite project environment
   

Requirements

• Experience with Playwright
• Experience with Python
• Experience with Apium
• Experience setting up AI automation solutions
• Experience with Copilot

About UN1Q
 

UN1Q is a pre-launch startup building an advanced fitness, nutrition and wellness coaching platform across mobile, web, smartwatch and AI-powered experiences. Our product combines structured coaching, personalization, exercise and nutrition planning, and increasingly AI-powered functionality. As we approach market launch, we need someone to own the stories we tell about it, and how they reach people.
 

The role

• Title: Content Creator (AI-first, fitness & wellness)
• Seniority: Mid-level (2–4 years)

You will own UN1Q's day-to-day content: planning it, writing it, producing it with AI-assisted workflows, publishing it and learning from the results. Most of our campaign content is AI-generated, so you will be fluent in the tools that make it and have the judgement to keep it accurate, on-brand and honest. You'll work closely with our Digital Designer, who owns brand visuals and hero campaign assets, and with Marketing and our CEO, who knows the product and its scientific methodology end to end.

What success looks like (first 6 months)

• A content strategy and 90-day launch calendar (pillars, platforms, formats, cadence) agreed with Marketing and the CEO.
• A steady weekly output across the agreed platforms, built on a documented AI-assisted workflow (prompts, templates, checklists) that others can follow.
• A tone-of-voice guide and a claims checklist, covering what we can and cannot say about training, nutrition and results, in daily use.
• Launch content (teasers, announcements, educational series) published on schedule.
• A monthly performance report with two or three clear learnings, such as which hooks and formats work, acted on the following month.

What you'll do

Strategy & planning

• Build content pillars and a launch calendar tied to product milestones.
• Turn product features and the coaching methodology into simple, accurate content for each platform.

Writing & scripting

• Write hooks, scripts, captions and short-form copy in UN1Q's tone of voice.
• Keep a bank of reusable formats and prompts so quality stays consistent as volume grows.

Production

• Produce short-form video (Reels, TikTok, Shorts), carousels and stories using AI tools and the templates provided by Design.
• Use AI for ideation, scripting, voiceover, clipping and repurposing: tools such as ChatGPT or Claude for drafts, Higgsfield, Seedance, Grok Imagine or Kling for video, GPT Image for stills, ElevenLabs for voice.
• Edit everyday content in CapCut (or comparable tools); brief the Digital Designer when a piece needs hero-level production.

Publishing & community

• Schedule and publish across channels; monitor and answer comments and messages within agreed guidelines.

Measure & improve

• Track views, retention, saves, shares, clicks and sign-ups; test hooks and formats; report monthly.

Quality & compliance

• Check content for accuracy and unsupported claims, with the CEO signing off anything new or borderline.
• Label realistic AI-generated content as required by the EU AI Act, keep a log of tools and sources, and respect music and likeness rights.
• Avoid content that promotes extreme dieting, unrealistic body ideals or unsafe training advice.

Must-haves

1. 2+ years creating and publishing social content for a brand or product, shown by a portfolio or live channel with measurable results.
2. Strong written English: hooks, scripts and captions in a clear, natural brand voice.
3. Short-form video editing in CapCut, DaVinci Resolve, Premiere or similar, with a feel for hooks, pacing, captions and retention.
4. Regular, hands-on use of AI tools in real production: LLMs for ideation and scripting, plus AI image and video generation (for example Higgsfield, Seedance, Grok Imagine, Kling, Runway, Veo or GPT Image) and AI voice (for example ElevenLabs). Tool-agnostic; what matters is publish-ready output.
5. Content planning: building and running a calendar, and scheduling in Meta Business Suite, Buffer, Hootsuite or similar.
6. Reading platform analytics (retention, saves, shares, clicks) and turning them into changes in what you make.
7. A careful, evidence-based approach to fitness, nutrition and wellness claims, and genuine interest in the subject.
8. Judgement on AI output and basic compliance: rejecting weak generations, labelling realistic AI content, and respecting music and likeness rights.
9. Works independently in a small remote team, juggles several priorities, and collaborates well with design and marketing.

Nice-to-haves

• Experience with fitness, nutrition, wellness, health-tech or consumer-app brands; a fitness or nutrition qualification is a plus, not a requirement.
• Community management and creator, ambassador or influencer collaborations.
• App-launch content: waitlists, app-store assets, testimonial and user-story content.
• Comfort on camera or on voiceover, if we later decide to use founder- or coach-led content.
• Additional languages, depending on launch markets.
• Experience testing creative variations and working with Canva, Adobe Audition or royalty-free libraries such as Envato.