Jobs ML / AI

Development of multiple AI Agents for internal functions of the large international enterprise.

#LI-

Requirements

• Mathematician or relevant education 
• Good understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, GBM, xGBoost , etc
• Practical experience with data mining and data visualization
• Python development experience 1+ years
• Good applied statistics skills, such as distributions, statistical testing, regression, etc. 

Nice to have:

• Practical experience with Rest API (Flask, Tornado)
• Practical experience with Tensorflow
• Experience with MapReduce, Hadoop, Spark
• Familiarity with Scala, Java 

Job responsibilities

• Undertaking data collection, preprocessing and analysis
• Analyze large amounts of information to discover trends and patterns
• Building models to address business problems
• Presenting information using data visualization techniques
• Collaborate with engineering and product development teams

About the Project:

We are building an international AI SaaS product and assembling a high-performance growth team focused on rapid experimentation and scalable user acquisition.

Our approach is data-driven: we test fast, iterate aggressively, and scale only what works.

We are looking for a designer who understands that the goal is not just to create visually appealing content, but to produce creatives that generate measurable results — clicks, conversions, and revenue.

Key Responsibilities:

- Create high-converting advertising banners for platforms such as Meta, TikTok, Google, Reddit, and others.

- Develop engaging video creatives, including UGC-style content, short-form ads, and performance-driven video formats.

- Adapt and scale competitor creatives while maintaining strong positioning and originality.

- Generate new creative concepts from scratch, including hooks, visual approaches, and messaging angles.

- Work actively with AI tools to significantly speed up content production and testing cycles.

- Collaborate closely with the growth and marketing team to test hypotheses and improve performance.

- Occasionally design landing pages and marketing presentations to support campaigns and product positioning.

Workload & Output Expectations:

- Produce 5–10 original creative concepts per week (completely new ideas and approaches).

- Create 10–15 adapted creatives per day based on competitor analysis and existing winners.

- Iterate quickly based on feedback and performance data, minimizing the number of revisions needed for approval.

Requirements:

- Proven experience in performance marketing creatives (not just branding or static design).

- Strong understanding of key metrics such as CTR, hook rate, and conversion rate.

- Ability to think in terms of marketing performance, not just design aesthetics.

- Experience in video production, especially UGC-style and short-form content.

- High proficiency with AI tools for generating images, videos, and content.

AI Stack (Must-Have)

- Midjourney / Stable Diffusion for image generation

- Runway / Pika for video generation

- CapCut / Premiere Pro / After Effects for editing

- NanBanana

- ByteDance tools (ModelArk / Seedream / video generation tools)

Additional Tools (Nice to Have)

- HeyGen / Synthesia / D-ID (AI avatars)

- ElevenLabs (AI voice generation)

- Face swap and lip-sync tools

- Any tools for scalable UGC production

Video Capabilities (Important)

- Ability to create native-looking UGC content that does not feel like traditional advertising

- Experience with AI voice-over, dubbing, and lip-sync

- Ability to replace faces and generate characters

- Capability to create video creatives fully from scratch using AI tools

Work Format

- Work as part of a cross-functional growth team (marketing, product, content)

- Execute tasks both based on briefs and through independent creative thinking

- Maintain fast communication and quick turnaround cycles

Mindset & Approach

We are looking for someone who is not just executing tasks mechanically.

It is important for us that you are engaged in the process, interpret each task through your own perspective, and bring your own ideas and improvements.

We value designers who take ownership, think proactively, and approach tasks with genuine involvement rather than simply following instructions.

Key Performance Indicators (KPI)

- CTR of produced creatives

- Number of revisions required before approval

- Speed of content production

- Percentage of creatives that enter testing

- Percentage of creatives that become winning assets

Compensation & Conditions

- Remote or hybrid format

- Fixed salary + performance-based bonuses

- Access to advanced AI tools and production resources

- Opportunity to grow into Lead Creative / Head of Creative role

Test Task

- Create 3 banner creatives for a single offer using different approaches (fear, benefit, curiosity)

- Produce 1 video creative (15–30 seconds, UGC or ad format)

- Use AI tools and clearly describe your workflow and tool stack

Evaluation Criteria

We do not evaluate based on visual beauty alone.

We focus on:

- Strength of the hook

- Creativity of the idea

- Likelihood of achieving high CTR

- Speed and efficiency of execution

We are looking for a Senior Data Scientist with strong technical expertise and a practical mindset to work on complex data-driven challenges. In this role, you will design and implement ML and GenAI solutions, experiment with modern approaches, and transform ambiguous business problems into scalable, production-ready systems.

Requirements
Must-have

• 4+ years of experience in Data Science
• 4+ years of hands-on experience with Python
• Strong understanding of Machine Learning fundamentals, including:
  • regression and classification models
  • feature engineering and model evaluation
• Practical experience with LLMs and GenAI, including:
  • GPT / ChatGPT or similar LLMs
  • LangChain
  • Retrieval-Augmented Generation (RAG)
• Experience with EDA, data preprocessing, and basic dimensionality reduction (e.g. PCA)
• Hands-on experience with tree-based models (e.g. XGBoost)
• Experience building scalable and high-load solutions
• Ability to write clean, maintainable code
• Participation in technical and architectural decisions
  
  Nice to have
• Experience with NLP libraries (SpaCy, Hugging Face)
• Understanding of Explainable AI (XAI) and model interpretability
• Experience with cloud platforms (AWS / GCP / Azure)
• Ability to translate business problems into ML solutions

• Background in R&D, experimentation, or prototyping

  
  Key Responsibilities

• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;
• Conduct R&D activities: explore new ML/GenAI techniques and assess their practical impact.
• Collaborate with engineering, product, and business teams to deliver impactful data-driven solutions.
  
  We offer:
• Great networking opportunities with international clients, challenging tasks;
• Building interesting projects from scratch using new technologies;
• Personal and professional development opportunities;
• Competitive salary nominated in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

   

Inception-1 is a product company that creates AI-driven B2C products designed to help people feel more connected and less alone. Our mission is to build meaningful digital experiences that blend technology with empathy — and to prove that technology can be both human and transformative.

We’re looking for a Technical AI Product Manager who will be responsible for delivery of AI-driven features of our product (which are the core) 
We want you to be responsible for solving complex user’s problems – delivering ready-to-use features and final value to user
This is hands-on role which requires mix of business acumen, team management and sufficient technical expertise in implementing visual and conversational AI models
Ideal candidate would have either experience of own AI-first project development (no, chat-bot is not there…) or managing the team of ML engineers with clear business impact. 
Both cases imply experience with agentic coding and AI tools/ agent integration - eg. you built pipeline with comfy for your companion/ developed support agents’ chain on n8n/ built context prompting architecture for your assistant/ etc. 

Responsibilities:

• Own the end-to-end product lifecycle with a strong technical focus: discovery, specification, delivery, and iteration.
• Act as a bridge between business and engineering: translate product goals into clear technical requirements and vice versa.
• Define product requirements for AI-powered features (logic, constraints, data dependencies, edge cases).
• Work closely with engineers to shape system architecture, API contracts, data flows, and technical trade-offs.
• Design, run, and interpret A/B tests, including experiments impacting AI behavior, personalization, and monetization.
• Prioritize roadmap, features, and technical debt based on business impact, system limitations, and user value.
   

Requirements:

• 2+ years of experience as a Product Manager in multi-purpose AI-first products (eg. not only conversational module, but also voice/ image generation/ video/ OCR/ etc.).

OR

• Founder of AI-first startup with seed round closed.
• Strong technical background (engineering, computer science, or equivalent hands-on experience).
• Rapid prototyping or scripting skills to validate ideas quickly.
• Hands-on experience in implementation of AI features, at least – API services, self-developed multi-purpose agents, etc.
• Ability to reason about trade-offs between speed, quality, scalability, and technical complexity.
• Excellent ability to align technical and non-technical stakeholders.
   

Nice to Have:

• Experience with AIAI companionship, social discovery, chat, or personalization system.
• Ability to read code and participate in technical discussions (even without being the primary implementer).
• Experience with prompt-based systems, model evaluation, AI quality metrics.
   

What We Offer:

• Real ownership — full responsibility for a core AI product used by millions worldwide.
• Technical impact — shape how AI systems are designed, shipped, and scaled in production.
• Entrepreneurial ecosystem — part of Genesis, with access to resources, funding, and the option to launch your own startup.

About us:

BetterMe — a global wellness ecosystem empowering millions to become better — physically, mentally, and emotionally. We build what makes people better and keep challenging ourselves to inspire others.

We are looking for an engineer who can build, configure, and optimize automations, including AI agents powered by modern LLM technologies.

Your impact:

• Improve and expand automation processes.
• Develop logic and prompts for multi‑step AI agents.
• Integrate agents with databases and APIs.
• Test, debug, and optimize agent performance.
• Maintain documentation and monitor agent efficiency.
• Strengthen AI expertise within the company and evolve solutions based on business needs.
• Identify new opportunities for applying AI solutions across the organization.
• Contribute to the development of AI‑related processes and infrastructure.

About you:

• 2+ years of experience with automation and AI tools.
• Understanding of LLM principles, prompt engineering, and OpenAI APIs.
• Strong proficiency in Python and SQL.
• Experience building production‑ready AI agents.
• Experience with LangChain / LlamaIndex / GPTs approach is a plus.
• Ability to quickly build MVP solutions.

What you get at BetterMe:

A mission that inspires. Every line of code, every design, every idea helps millions of people become healthier and more confident.
Trust without micromanagement. You manage your time and make decisions independently. We value outcomes, not online hours.
Growth opportunities. 90% of our leads have grown within the company. There’s space for initiative, new responsibilities, and real career upgrades.
Flexible work format. Choose what works best for you — office, remote, or hybrid.
Wellness in practice. Offline: workouts with professional trainers in our corporate gym, massage, corporate lunches, sports, and team activities — everything you need to recharge and reset together. Online: regular online workouts, partner discounts, and free access to our products.
Health insurance & corporate doctor.
Time off & balance. 20 paid vacation days, paid sick leave, and additional days off around public holidays.
Open communication. Transparency across teams, honest feedback, and support for initiatives are part of our everyday culture.
Support for sports events. We cover entry fees and encourage the team to compete and participate together.
Modern equipment. We provide new hardware and everything you need for productive work.
Legal & finance support. Experienced lawyers and financial specialists are always there to help — from documents to personal consultations.

🌍 Job Title:

Senior Full-Stack Research Engineer

🧩 Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

🌟 About the Product:

This platform provides an AI-driven intelligence layer for real estate underwriting, focusing on short-term bridge financing. It ingests diverse public and user-submitted property data—ranging from financial documents and renovation plans to market listings—and applies OCR, classification, schema extraction, and large language models to deliver comparable asset analysis and risk scoring. 

💻 About the Role:

As a Senior Full-Stack Research Engineer on our AI research team, you will drive end-to-end development from hypothesis and prototyping to production deployment. You will design, build, and optimize critical pipelines that extract, classify, and reason over complex financial and property documents using frameworks such as DSPy and LangGraph. You will implement and maintain FastAPI services and TypeScript integrations, ensuring system resilience, observability, and scalable data aggregation. 

📌 Key Responsibilities:

• Optimize AI flow pipelines (OCR → classify → extract) using LangGraph and DSPy to reduce error rates and latency on financial and property documents.
• Orchestrate fault-tolerant, agentic workflows that connect document classification, OCR, and schema extraction modules into cohesive state machines.
• Conduct gap analyses with custom evaluation suites, measure precision and recall, and implement prompt/evaluation loop improvements and multi-step reasoning strategies.
• Prototype LLM-based models in Jupyter Notebooks and productionize them via FastAPI endpoints and TypeScript client integrations.
• Build and scale data aggregation systems, normalize heterogeneous schemas, and resolve conflicts across external real estate datasets.
• Implement robust caching, retry logic, and observability (tracing, structured logging) to maintain resilience against service outages.
• Translate research prototypes into tested, containerized services and integrate them into CI/CD pipelines.
• Collaborate on defining the architecture and establish a standard research-to-release playbook for upcoming AI initiatives.

📝 Required Competence and Skills:

• 5+ years as a backend developer, with recent experience driving end-to-end AI research and applying LLMs for verification (prompt/evaluation loops) and broader problem solving.
• Experience working on AI-centric products, contributing to both backend development and the integration of AI as a core component of the system.
• Proficiency in Python or Node.js.
• Understanding of LLM orchestration tools (e.g., LangGraph), prompt optimization frameworks (e.g., DSPy), vector retrieval systems (e.g., Weaviate, Elasticsearch), and multi-model integrations (OpenAI, Gemini, vLLM).
• Strong skills in Docker, container orchestration, message queues, CI/CD, and observability practices.
• Demonstrated ability to design complex data schemas and perform multi-source data fusion.
• Comfortable using Jupyter Notebooks for rapid experimentation, benchmarking, and metric-driven prototyping.
• Experience with document pipelines, including OCR, parsing, classification, and handling noisy real-world inputs.

➕ Nice to Have:

• TypeScript in strict mode with Zod schema validation.
• Graph database modeling experience with Neo4j.

🚀 Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

COMPANY

Arcyn is a freshly funded seed stage startup. We’re creating an AI-powered compliance checker for architectural design — an Autodesk Revit plugin that automatically checks designs against regulations as they're being created. Architects get instant feedback on violations as they design in Revit, instead of waiting weeks for permit reviewers to tell them what's wrong.

We’ve just closed pre-seed round and are building core technical team. We’re now a team of 4 with a track record of building complex technical products, and we're looking for a strong AI engineer who's comfortable testing hypotheses and working across different frameworks. This is a chance to join at the ground floor, shape product architecture and solve genuinely hard AI problems.

----

In this role, you'll architect AI systems from scratch and own the full development cycle, there's plenty of room for experimentation and rapid iteration. We're seeking a highly skilled AI Engineer with strong experience in orchestrating multi-step LLM workflows, automated code generation, and compliance logic formalization.

RESPONSIBILITIES: 
• Design and maintain modular, multi-step AI workflows for compliance automation. 
• Integrate multiple LLM providers (e.g., OpenAI, Anthropic, Perplexity) into a cohesive orchestration pipeline. 
• Build cost-optimized batch processing and intelligent API request strategies. 
• Translate complex regulations into structured, machine-executable logic. 
• Develop and validate automatically generated code to ensure correctness, safety, and performance. 
• Collaborate with domain experts to refine logic interpretation and edge case handling. 

• Maintain high-quality, well-structured Python codebases with clear separation of concerns. 

REQUIREMENTS  
• 5+ years of professional software engineering experience. 
• Strong Python skills, including experience writing production-grade, modular code. 
• Proven track record building multi-step LLM workflows (LangChain, LangGraph, or similar). 
• Experience in structured code generation and validation. 
• Strong debugging skills and comfort working with complex, evolving systems. 

   NICE TO HAVEs: 
   • Experience with compliance automation, technical regulations, or domain-specific rule translation. 
   • Familiarity with Pydantic models or other type-safe data management frameworks. 
   • Background in developer tooling or systems requiring high reliability and reproducibility. 
   • Experience optimizing LLM API usage for both cost and speed. 

WE OFFER:

• B2B set-up via SP account
• Full-time remote role aligned with EEST
• Be part of the team shaping a new AI product at an early stage. 
• Freedom to architect solutions using the best tools for the job. 
• Collaboration with a multidisciplinary, innovation-driven team. 
• Flexible work arrangements and competitive compensation.

N-iX is looking for a Lead Machine Learning Engineer (Computer Vision) to join our external expert network.
 

We are looking for a Lead-level ML expert who will support our hiring process by conducting technical interviews and evaluating candidates according to our internal competency matrix.

This is not a full-time project role, but a flexible collaboration where you will participate in technical interviews when needed.

We are looking for a Lead-level ML expert who will support our hiring process by conducting technical interviews and evaluating candidates according to our internal competency matrix.

This is not a full-time project role, but a flexible collaboration where you will participate in technical interviews when needed.

Responsibilities

• Conduct technical interviews for ML / Computer Vision candidates
• Evaluate candidates according to competency matrix
• Assess both practical experience and theoretical knowledge
• Provide clear and structured feedback after interviews
• Validate real-world experience in building and deploying ML solutions

 Requirements

• 6+ years of experience in Machine Learning / Computer Vision
• Experience taking ownership of technical solutions (design, decision-making, mentoring or leading initiatives)
• Strong hands-on engineering background
• Experience working with production ML systems
• Upper-Intermediate English or higher
  Strong hands-on experience with PyTorch or TensorFlow
• Solid understanding of end-to-end ML lifecycle
  Experience with model deployment and inference optimization
• Experience with experiment tracking tools
  (MLflow, Weights & Biases, DVC or similar)
• Understanding of distributed training concepts

 Nice to have

• Experience with model optimization tools (ONNX, TensorRT, OpenVINO, etc.)
• Experience with cloud platforms (AWS, GCP, Azure)
• Experience mentoring engineers or conducting interviews

We are seeking a Senior AI Engineer to join our engineering team and lead the effort in modernizing our e-commerce platform with AI capabilities. You will be responsible for the architecture, development, and integration of advanced AI systems, including Retrieval-Augmented Generation (RAG) pipelines, autonomous agents, and fine-tuned language models, within a mature, enterprise-grade .NET environment. Besides hands-on engineering, you will influence technical direction, mentor fellow engineers, and play a key role in shaping our long-term AI strategy.

Key Responsibilities

• Lead the design and implementation of production-grade RAG architectures that connect large language models to proprietary product, customer, and operational data.
• Architect and build AI agent systems that automate complex e-commerce workflows, including customer support, merchandising, and order management.
• Drive the strategy and execution of fine-tuning foundation models on domain-specific datasets to enhance relevance, accuracy, and business alignment.
• Evaluate, select, and integrate third-party AI services and APIs (e.g., OpenAI, Anthropic, Amazon Bedrock) into existing .NET applications and microservices.
• Define and promote best practices for prompt engineering, evaluation frameworks, model versioning, and responsible AI use across the engineering organization.
• Collaborate closely with backend, frontend, data engineering, and product teams to deliver end-to-end AI features within the current platform architecture.
• Own the performance, reliability, cost optimization, and observability of AI systems in production.
• Mentor mid-level and junior engineers, conduct code reviews, and raise the technical standard of the team.

• Proactively identify high-impact opportunities where AI can generate measurable business value.

   

What we are looking for:

• 7+ years of professional software engineering experience, including at least 3 years focused on machine learning or AI engineering.
• Extensive hands-on experience developing LLM-based applications, such as RAG, agent frameworks, and model fine-tuning in production environments.
• Strong proficiency in C# / .NET with proven experience managing enterprise-scale .NET codebases.
• Solid knowledge of Python for ML experimentation, training pipelines, and prototyping.
• Experience working with vector databases (e.g., Qdrant, Weaviate, Milvus, Amazon OpenSearch, Pinecone) in production.
• Proficiency with orchestration frameworks like Semantic Kernel, LangChain, or AutoGen.
• Strong understanding of RESTful APIs, microservices architecture, and distributed systems on AWS.
• Proven ability to make architectural decisions and communicate technical trade-offs to both engineering and non-technical stakeholders.
• Track record of leading complex technical initiatives from design to production deployment.
• Strong analytical skills and the ability to translate ambiguous business problems into clear, well-defined AI solutions.

Nice to have:

• Experience in the e-commerce domain (catalog, search, recommendations, personalization, customer service).
• Hands-on experience with MLOps practices, including model deployment, monitoring, A/B testing, and CI/CD for ML pipelines.
• Familiarity with AWS AI and ML services such as Amazon Bedrock, Amazon SageMaker, Amazon Comprehend, and Amazon Kendra.
• Practical experience working with AWS infrastructure services like Lambda, ECS, Step Functions, and S3 in AI workloads.
• Knowledge of embedding models, re-ranking strategies, and semantic search optimization at scale.
• Experience with platform modernization or large-scale migration projects in enterprise environments.
• Experience mentoring engineers or leading technical guilds and working groups.
• Contributions to open-source AI/ML projects or published research.

Why join Empeek?

• A high-impact role leading AI transformation within an established enterprise platform.
• A collaborative, experienced engineering team with a strong focus on modernization.
• Significant autonomy and influence over technical direction.
• Access to cutting-edge tools, models, and cloud infrastructure.
• Competitive compensation package (discussed during the interview process).
• Opportunities for professional development and continuous learning.

What we offer:

• Access to internal and external training, certification reimbursement;
• 18 working days of paid vacation, 10 compensated public holidays, and up to 10 paid sick days;
• Up to $300/year for English classes + a free speaking club;
• Up to $180/year for sports activities;
• A strong culture of knowledge sharing with senior experts you can really learn from;
• New equipment provision, and accounting support if needed;
• Competitive market-level salary with regular performance and salary reviews;
• Extra perks such as an insurance fund, seasonal gifts, celebrations, and additional team compensations;
• A psychologically safe and supportive environment;
• Active social responsibility and continuous support for the Armed Forces.

If you believe this role could be a great match for you, please send us your resume via the link — we’ll be happy to get in touch with you.

You’re also welcome to recommend colleagues or friends — we offer a referral bonus 🎁.

We’re looking for an experienced ML/NLP engineer to analyze ~700k job records and identify niches and sub-niches.

Scope:

• Generate embeddings from job titles/descriptions
• Cluster jobs into meaningful groups (niches)
• Create sub-clusters (sub-niches)
• Auto-label clusters using LLMs
• Provide clean structured output

Requirements:

• Experience with embeddings (OpenAI or sentence-transformers)
• Clustering (HDBSCAN, KMeans)
• Python (pandas, scikit-learn)
• Experience with large datasets

Nice to have:

• FAISS or vector DB experience
• Previous work with marketplace/job data

Deliverables:

• Script/pipeline
• Clustered dataset
• List of niches with labels

To apply:
Please share a similar project you’ve done and briefly explain your approach.

Domain: Audio/Sound recording
Job Description

Qualifications:

• 3+ years of experience in Machine Learning Engineering, Applied AI, or related roles, with experience building and shipping production applications.
• Hands-on experience developing applications with LLMs (e.g., OpenAI APIs, open-source models, LangChain, LlamaIndex, or similar).
• Strong proficiency in Python and experience building scalable, user-facing systems or APIs.
• Experience designing and deploying interactive or real-time AI systems.
• Solid understanding of LLM concepts, including prompt engineering, retrieval-augmented generation (RAG), and model evaluation.
• Familiarity with cloud-based ML infrastructure (AWS, SageMaker, or similar), with the ability to collaborate effectively with MLOps teams.
• Clear grasp of latency, cost, and performance trade-offs when serving LLMs in production.
• Bonus: Familiarity with music production workflows, DAWs, or audio plugins.

Education:

• Bachelor’s or Master’s degree in Computer Science, related technical field, or equivalent practical experience.

Job Responsibilities

You will develop customer-facing AI experiences and contribute to the systems that support them. This includes:

• LLM Application Development: Design and build interactive, user-facing LLM-powered features such as virtual assistants, creative copilots, and intelligent workflow tools integrated into our products.
• Product Integration: Work closely with product, design, and audio engineering teams to embed AI capabilities directly into DAWs, plugins, and user-facing platforms.
• LLM Deployment & Optimization: Implement efficient, low-latency model serving strategies for real-time user interactions, balancing performance, cost, and responsiveness.
• Prompt & Interaction Design: Develop robust prompt engineering and response strategies tailored to creative workflows, ensuring high-quality, context-aware user experiences.
• Collaboration with ML Platform Teams: Partner with cloud and infrastructure engineers to leverage and extend existing pipelines (e.g., AWS SageMaker) for production deployment.
• User-Centric Iteration: Analyze usage patterns and feedback to continuously improve AI-driven features and ensure they provide clear value to musicians and creators.

Department/Project Description

The company is looking for a Machine Learning Engineer to help build and deliver next-generation AI-powered experiences for our customers. This role focuses on developing outward-facing LLM applications, such as intelligent assistants, creative tools, and interactive features integrated into our digital audio workstation and plugin ecosystem.

While you will work with state-of-the-art Large Language Models and collaborate with infrastructure teams, the core of this role is application development: designing, building, and deploying engaging, real-time AI features that enhance music creation workflows and delight our users.

Description

We are building an AI-driven SDLC automation platform leveraging AWS Bedrock, knowledge bases, domain agents, and tool-based orchestration.
We are looking for engineer to implement the AI architecture, including RAG pipelines, agent systems, tool-calling mechanisms (MCP-style architectures), model evaluation, and guardrails.
This role requires real production GenAI experience, not experimentation.

Requirements

• 4+ years of software engineering experience
• 2+ years of hands-on ML / AI engineering experience
• Strong Python (mandatory)
• Proven production experience with LLM systems
• Deep understanding of:

– RAG architecture

– Embeddings

– Chunking strategies

– Retrieval optimization

• Experience with AWS Bedrock
• Experience designing tool-calling LLM systems (MCP or equivalent architecture)
• Experience integrating external APIs as agent tools
• Experience building REST services (FastAPI or similar)
• Experience with vector databases (OpenSearch, Pinecone, etc.)
• Experience implementing evaluation frameworks for LLM quality
• Experience mitigating hallucinations and prompt instability
• Strong understanding of:

– Token economics

– Context window constraints

– Cost-performance tradeoffs

• Experience integrating with GitHub and JIRA APIs
• Production experience beyond notebooks or PoCs

Job responsibilities

• Implement RAG pipelines on AWS Bedrock
• Implement knowledge ingestion pipelines (JIRA, GitHub, Confluence, S3)
• Define chunking, embedding, and retrieval strategies
• Implement vector storage and retrieval architecture
• Architect tool-calling agent systems (MCP or equivalent)
• Define when to use:
• – Direct API invocation
• – Lambda-based tools
• – MCP-based tool integration
• – Design and implement structured output agents
• Implement hallucination mitigation strategies
• Build evaluation pipelines for model quality and regression testing
• Optimize token usage and latency
• Implement guardrails and structured validation
• Work closely with DevOps to productionize AI services

We are a fast-growing AI-powered fintech company building an AI-first operating environment across the business.

We are looking for a hands-on Agentic Deployment Expert to help us deploy AI across multiple departments, build practical agent-based workflows, and maintain the infrastructure behind them.

This role is for someone who moves fast, experiments constantly, and knows how to turn AI tools into real business leverage.

What you will do

• Deploy and improve AI agents across different company departments
• Identify repetitive workflows that can be automated or improved with AI
• Build and maintain internal AI tooling and supporting infrastructure
• Work with Docker, Telegram bots, cloud environments, and AI products
• Optimize infrastructure costs while keeping systems scalable
• Maintain strong security standards, including encryption and safe AI stack usage
• Continuously test new AI tools, models, and releases, then decide what is worth implementing
• Help shape and maintain an AI-first internal operating environment

What we are looking for

• Mid or Senior-level specialist
• Strong hands-on experience with AI tools, agentic workflows, or automation
• Solid experience with Docker
• Experience building or supporting Telegram bots
• Good understanding of cloud infrastructure
• Fast execution and strong ownership
• Strong interest in the fast-moving AI ecosystem

Ability to evaluate new tools critically and apply them to real business needs

Would be a plus

• Experience in fintech or other fast-moving product environments
• Experience optimizing infrastructure costs
• Experience with security and encryption best practices

Experience deploying AI solutions across multiple business functions

What we offer

• Opportunity to shape AI adoption across the whole company
• Real ownership and high-impact work
• Fast-moving AI-first environment
• Fully remote format
• Full-time cooperation

We are building an AI-driven SDLC automation platform leveraging AWS Bedrock, knowledge bases, domain agents, and tool-based orchestration.

We are looking for a Lead AI Engineer to design and implement the AI architecture, including RAG pipelines, agent systems, tool-calling mechanisms (MCP-style architectures), model evaluation, and guardrails. This role requires real production GenAI experience, not experimentation.

Requirements: 

• 8+ years software engineering experience
• 3+ years hands-on ML / AI engineering experience
• Strong Python (mandatory)
• Proven production experience with LLM systems
• Experience with AWS Bedrock
• Experience designing tool-calling LLM systems (MCP or equivalent architecture)
• Experience integrating external APIs as agent tools
• Experience building REST services (FastAPI or similar)
• Experience with vector databases (OpenSearch, Pinecone, etc.)
• Experience implementing evaluation frameworks for LLM quality
• Experience mitigating hallucinations and prompt instability
• Experience integrating with GitHub and JIRA APIs

• Production experience beyond notebooks or PoCs

   

Deep understanding of:

• RAG architecture
• Embeddings
• Chunking strategies
• Retrieval optimization

Strong understanding of:

• Token economics
• Context window constraints
• Cost-performance tradeoffs

Responsibilities: 

• Architect and implement RAG pipelines on AWS Bedrock
• Design knowledge ingestion pipelines (JIRA, GitHub, Confluence, S3)
• Define chunking, embedding, and retrieval strategies
• Design vector storage and retrieval architecture
• Architect tool-calling agent systems (MCP or equivalent)
• Design and implement structured output agents
• Implement hallucination mitigation strategies
• Build evaluation pipelines for model quality and regression testing
• Optimize token usage and latency
• Define model routing strategies (cost vs quality)
• Implement guardrails and structured validation
• Work closely with DevOps to productionize AI services
• Mentor AI engineers and define AI engineering standards
• Define long-term GenAI roadmap and architecture patterns

• Define when to use:

   

  – Direct API invocation

  – Lambda-based tools

  – MCP-based tool integration

What is in for You: 

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

COMPANY
Atlas Technica is a fast-growing US-based MSP working with hedge funds and investment firms.
Founded in New York in 2016, the company has grown to 200+ engineers across 10+ countries (US, UK, Ukraine, Hong Kong, Singapore).
Atlas Technica combines product-level engineering standards with a strong service culture, partnering directly with top-tier investment firms on their digital transformation and automation initiatives.

We are seeking an AI Engineering professional to join our DevOps team. The goal of this role is to design and deploy intelligent chatbots using Azure Bot Framework, OpenAI, and Cognitive Services. Build data pipelines and fine-tune NLP models with Azure ML. Integrate AI with enterprise systems via RESTful APIs, ensuring compliance with security and privacy standards. Stay current with LLM advancements and collaborate across teams.

Location/Type: Remote
Hours: 10 AM-7 PM UA

Hiring process: 2 interviews
 

Responsibilities

AI Agent & Chatbot Development
• Design, build, and deploy intelligent conversational agents using Azure Bot Framework, Azure OpenAI, and Cognitive Services.
• Develop prompt strategies and manage datasets to support context-aware, multi-turn dialogue and accurate responses.
• Conduct rapid prototyping to validate technical feasibility and demonstrate the business value of AI-driven solutions.

Data & Model Engineering
• Build and maintain robust data pipelines to support training and inference workflows.
• Configure, train, and fine-tune machine learning models using Azure Machine Learning, with a focus on NLP and LLMs.
• Evaluate and optimise AI system performance for accuracy, scalability, latency, and cost-efficiency.

System Integration & Architecture
• Architect and implement integration between AI and enterprise systems (e.g., ConnectWise Manage, Confluence, etc) using RESTful APIs.

Security, Compliance & Governance
• Ensure AI systems comply with data privacy regulations (e.g., GDPR) and enterprise-grade security standards.
• Implement access controls, data encryption, and audit logging for sensitive AI workflows.

Research & Innovation
• Stay current with evolving LLM technologies, frameworks and methodologies.
• Evaluate emerging tools and techniques to improve solution quality and delivery speed continuously.

Collaboration & Leadership
• Work closely with cross-functional teams to interpret business requirements and recommend LLM-driven solutions.
• Contribute to technical and architectural decisions, ensuring alignment with strategic goals.

Requirements:

• English level — B2 or higher
• 4+ years of experience in ASP.NET software development (Core/WebAPI, C#, React/React.js), with a focus on AI engineering and Azure-based solutions.
• Experience building intelligent chatbots and autonomous agents (Agentic AI) that perform real actions, plan, reason, and act with minimal human input; familiar with multi-agent orchestration and agent memory.
• Advanced expertise in machine learning, deep learning, and NLP, including pipelines, model fine-tuning, embeddings, and transformer-based architectures.
• Strong understanding of large language models (LLMs), their limitations, and modern capabilities (e.g., GPT, Claude, Gemini), as well as practical experience with Retrieval-Augmented Generation (RAG) and optimising retrieval pipelines.
• Hands-on experience with Azure AI services (Azure Machine Learning, Cognitive Services, Bot Framework) and knowledge of MCP or similar protocols for secure, scalable integration between AI agents and enterprise systems.
• Familiarity with deploying, monitoring, and maintaining ML models in production environments.
• Ability to write clean, maintainable, and testable code following SOLID principles and Clean Architecture patterns.

Desirable Qualities

• Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms.
• Familiarity with CI/CD pipelines and DevOps practices.
• Experience with Azure Cosmos DB.
• AI-102
• Prior experience integrating AI agents with enterprise platforms like ConnectWise Manage, Confluence, SPO, etc.