Jobs ML / AI

AI Systems Engineer (LLM / Agents / RAG)

Remote | Full-time | Flexible Schedule

Our client is looking for a strong AI Systems Engineer to help design and build production-grade AI infrastructure, agent-based systems, and workflow automation.

You’ll work directly with the Head of AI on building the company’s internal AI ecosystem: multi-agent systems, RAG pipelines, AI-powered analytics, automation workflows, integrations, and operational AI tooling.

This role is ideal for someone who enjoys building real AI systems end-to-end — not just experimenting with prompts, but designing scalable architectures and shipping production-ready solutions.

Responsibilities

• Design and develop production AI/LLM systems
• Build agent-based workflows and multi-agent orchestration systems with memory, routing, and tool usage
• Develop end-to-end RAG pipelines and knowledge base systems:
  • ingestion
  • chunking
  • embeddings
  • retrieval
  • vector databases
  • citation tracing
  • hallucination mitigation
• Build AI-powered workflow automation for marketing, analytics, operations, and reporting
• Integrate LLM systems with CRMs, APIs, external platforms, and internal tools
• Develop integrations using REST APIs, webhooks, and third-party services
• Participate in building unified analytics and attribution systems across multiple channels and platforms
• Support creative/content AI pipelines (image/video generation workflows)
• Improve reliability, observability, latency, and cost-efficiency of AI systems
• Deploy and maintain AI systems in production environments
• Work closely with the Head of AI on architecture and AI ecosystem development

Requirements

• 2+ years of hands-on experience building production AI/LLM systems (not educational or pet projects)
• Strong Python skills
• Experience building production backend systems and integrations
• Practical experience with:
  • agent orchestration frameworks (LangGraph-class frameworks)
  • tool/function calling
  • structured outputs
  • guardrails
  • multi-agent systems
• Strong understanding of RAG systems and retrieval pipelines
• Experience with vector databases:
  • Pinecone
  • Qdrant
  • pgvector
• Experience with PostgreSQL and data-layer architecture
• Understanding of:
  • embeddings
  • chunking strategies
  • retrieval quality
  • citation tracing
  • hallucination mitigation
• Experience with workflow automation tools:
  • n8n
  • Make
  • Zapier
  • or similar
• Basic LLMOps understanding:
  • evals
  • observability (Langfuse-class tooling)
  • latency optimization
  • cost optimization
  • fallback model chains
• Experience working with OpenAI and/or Anthropic Claude APIs
• Understanding of MCP (Model Context Protocol)
• Experience with REST APIs, webhooks, and external integrations
• English level: B1+

Nice to Have

• Experience with AI automation for marketing, analytics, or operations
• Experience with e-commerce ecosystems:
  • Shopify
  • Amazon
  • TikTok Shop
  • marketplace analytics
• Experience with attribution or marketing analytics systems
• Experience with image/video generation workflows or ComfyUI
• Understanding of privacy/compliance concepts (CCPA-class requirements)
• Portfolio or GitHub with production AI projects

What Matters in This Role

• Strong ownership mindset
• Ability to translate business problems into working AI architectures
• Production-oriented engineering mindset
• Ability to work independently in async environments
• Focus on measurable and reliable AI systems rather than experimental demos

We Offer

• Fully remote work from anywhere
• Flexible schedule
• Direct collaboration with the Head of AI
• Modern AI stack and real production AI challenges
• High ownership and technical freedom
• Paid vacation and sick days

About the Role

We are looking for a strong engineer who can help us build AI-powered tools and automation for real business problems.

We work with large amounts of business data and are building internal systems for verification, enrichment, and automation. We need someone who can quickly understand a problem, suggest a practical solution, and build it.

This role is very hands-on. We are looking for a builder — someone who likes solving problems, moving fast, and turning ideas into working products.

What You’ll Do

• Build AI agents and automation workflows
• Work with LLMs (OpenAI, Claude, etc.)
• Build tools that help automate manual work
• Integrate APIs and external systems
• Improve speed, quality, and reliability of workflows
• Quickly test ideas and move them into production
• Work closely with business and product teams

What We’re Looking For

Must Have

• Strong Python skills
• Experience building real products, systems, or automation
• Experience working with LLMs and AI tools
• Experience with APIs and integrations
• Ability to solve problems independently
• Fast execution and ownership mindset

Strong Plus

• Deep experience with AI-native development workflows
• Daily use of Claude Code, Codex, Cursor, or similar agentic coding tools
• Experience building products using AI-assisted engineering environments

Nice to Have

• Experience with LangGraph, CrewAI, AutoGen, or similar frameworks
• Experience with RAG, vector databases, or AI memory systems
• GitHub or personal projects
• Experience working with large amounts of data

Important

We are not looking for someone who only builds no-code automations.

We are looking for someone who can understand a business problem, think through the solution, and build working systems.

Please share examples of projects you built and your GitHub (if available).

We Offer

• Remote work
• Long-term collaboration
• High-impact projects
• Modern AI tools and technologies
• Fast-moving environment

We are looking for a Senior Software Engineer who operates at the intersection of high-scale full-stack engineering and cutting-edge Applied AI.
 

In this role, you won’t just "write code", you will design and ship intelligent, cloud-native systems for our Maritime Intelligence Agentic platform. Our systems are used by different organizations to secure trade and enforce compliance at sea. You will be expected to work autonomously, influence our core architecture, and significantly raise the bar for AI-assisted development within the team.
 

What You’ll Do

• Architect & Build: Design and deliver agentic workflows and scalable microservices, primarily using Python, within a distributed system architecture.
• AI Integration: Lead the integration of Generative AI capabilities, including LLM APIs, RAG pipelines, and agentic workflows into our production systems.
• Agentic Operations & Observability: Implement operational practices, observability, and autonomous monitors (e.g., detecting intelligence drift or hallucinations) to ensure AI reliability in production.
• Elevate Engineering: Drive overall engineering quality and speed by implementing AI-SDLC practices, ensuring high standards through rigorous code reviews, test automation, and by establishing continuous, trace-based quality evaluation for all software and agentic components.
• Mentor & Innovate: Evaluate emerging AI tooling, mentor fellow engineers, and contribute directly to our technical roadmap.

Who You Are

• A Professional Engineer: You have 5+ years of professional full-stack or backend engineering experience, including 2+ years of experience building agents or agentic workflows in production at scale within a distributed system architecture.
• An AI-Native Engineer: You are excited about agentic development and agent-based operations. You are proficient in high-scale AI-based development, utilizing tools like Claude Code, Cursor, or Copilot in a highly autonomous fashion, and are a strong, independent individual contributor who can work effectively alone or in small, ad-hoc groups.
• Distributed & Cloud Architecture: You have proven experience with GraphQL or REST and designing scalable, cloud-based distributed architectures, including event-driven patterns. You are comfortable with AWS (K8S, Serverless, Event-driven), messaging (SQS, SNS) and databases (PostgreSQL, DynamoDB, MongoDB). Experience with Vector DBs is a plus.
• A Craftsman: You take pride in clean code, thoughtful design, and production-grade security, operations and observability. You are accountable, independent, and thrive in ambiguous environments.

Technical Requirements

• Agentic Frameworks (Mandatory): Proven expertise building autonomous agentic systems using frameworks such as LangChain, LangGraph, DeepAgents, CrewAI, OpenClaw, or Hermes (or able to demonstrate equivalent expertise on another relevant framework).
• Backend Languages: Fluent in Python (preferred) or TypeScript/Go/Rust, with proficiency in transitioning to Python.
• Infrastructure & IaC: A solid background with the AWS stack, including Kubernetes (K8S), Terraform (IaC), and CI/CD is essential (Helm is a strong plus).
• Nice to Have: Experience with frontend stack (NextJS, React.js, or similar)

We seek a Strong Middle ML / AI Engineer to join our team on a humanitarian transparency platform. This is a hands-on engineering role focused on building machine learning models and data pipelines — primarily around deduplication, anomaly detection, and statistical analysis of humanitarian data.

 

🧙‍♂️ In This Role You Will

• Design, build, and maintain ML models for deduplication, anomaly detection, and predictive analytics.
• Work with structured humanitarian data — beneficiary records, financial transactions, procurement flows.
• Build and maintain data processing pipelines using Python (Pandas, NumPy, scikit-learn).
• Collaborate with the backend team to expose ML/AI outputs via APIs.
• Monitor model performance and iterate based on real-world feedback.
• Document your work and support knowledge sharing within the team.
  
  
   

🎯 You May Be Interested If

• You enjoy working with messy, real-world data and turning it into reliable ML outputs.
• You care about model quality, reproducibility, and practical impact.
• You're comfortable applying classical ML approaches to solve concrete business problems.
• You're excited to collaborate in a remote, cross-functional environment.
• You value autonomy, clear communication, and working in a supportive, small-team setting.
  
   

👌 Role Requirements

• 3+ years of experience in ML engineering, data science, or a closely related role.
• Strong Python skills: Pandas, NumPy, scikit-learn.
• Experience building and deploying ML models in production environments.
• Solid understanding of data pipeline design and data quality practices.
• Familiarity with cloud platforms (Azure or AWS) for ML workloads.
• Proficiency with Git and standard development tooling.
• English proficiency at B1 level or higher.
   

Nice to have:

• Experience with PyTorch or TensorFlow.
• Hands-on experience with LLM integrations (OpenAI, Anthropic, or similar).
• Familiarity with ML experiment tracking tools (e.g. MLflow, Weights & Biases).
• Experience with GIS or geospatial data.
• Background in fraud detection, entity resolution, or deduplication tasks.
• Familiarity with Docker and CI/CD workflows for ML pipelines.
  
   

💻 Working Conditions

• Employment Type: Full-Time
• This is a fully remote position with the entire team across Ukraine.
• 20 working days of paid vacation per year.
• The team collaboratively defines deadlines, ensuring a balanced and manageable workload. The focus is on delivering commitments on time.
• Flexible working hours to promote a healthy work-life balance.

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of an AI product company in advanced manufacturing.
• Be part of a research focused team.

Responsibilities: 

• Research, test and develop generative AI based solutions.
• Collaborate with mechanical engineers to enhance your research.
• Design and implement end-to-end AI solutions that integrate with existing systems.
• Collaborate with software engineers and product teams to understand business needs and translate them into technical solutions. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. 
• Proven experience in developing generative AI or machine learning models.
• Commercial experience in using large language models.
• Programming skills in languages such as Python or JavaScript.
• Familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Computer Vision Engineer to join a project with a global leader in biomedical imaging. The company offers a comprehensive product portfolio for Karyotyping, H&E, IHC, and FISH analysis, providing advanced imaging and analysis tools for Pathology, Cytogenetics, and Research laboratories. This role involves working on cutting-edge solutions that enable high-precision diagnostics and support innovation in scientific research.

Key Requirements:

🔹 5+ years of hands-on experience in algorithm development using Python (must) and C++ (advantage);
🔹 Proven experience in training, fine-tuning, and deploying AI/ML models – Must;
🔹 Experience in Computer Vision (e.g., Shape Analysis) / Image Processing using image processing libraries like OpenCV in C++ – Advantage;
🔹 Strong ability to work independently as well as in a SCRUM team under Agile dynamic environment; proactive and self-driven;
🔹 Methodical, solution-oriented mindset with a strong “can-do” approach;
🔹 MSc or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Physics, or a related field – Must;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Research and develop advanced algorithms in Machine Learning, Neural Networks, Computer Vision, Image & Signal Processing, to be integrated into ASI products;
🔹 Define software specifications and deliver production-ready code that meets project milestones, while addressing constraints such as computational resources, response time, and memory consumption (GPU and CPU);
🔹 Train, optimize, validate and Integrate AI/ML models for diagnostic and imaging applications using Python and its libraries (PyTorch, NumPy, etc);
🔹 Collaborate closely with cross-functional teams, including R&D, Applications, and Product groups;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;
 

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.

We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.

Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Computer Vision Engineer to join a project with a global leader in biomedical imaging. The company offers a comprehensive product portfolio for Karyotyping, H&E, IHC, and FISH analysis, providing advanced imaging and analysis tools for Pathology, Cytogenetics, and Research laboratories. This role involves working on cutting-edge solutions that enable high-precision diagnostics and support innovation in scientific research.

Key Requirements:

🔹 5+ years of hands-on experience in algorithm development using Python (must) and C++ (advantage);
🔹 Proven experience in training, fine-tuning, and deploying AI/ML models – Must;
🔹 Experience in Computer Vision (e.g., Shape Analysis) / Image Processing using image processing libraries like OpenCV in C++ – Advantage;
🔹 Strong ability to work independently as well as in a SCRUM team under Agile dynamic environment; proactive and self-driven;
🔹 Methodical, solution-oriented mindset with a strong “can-do” approach;
🔹 MSc or PhD in Biomedical Engineering, Electrical Engineering, Computer Science, Physics, or a related field – Must;
🔹 English – Upper-Intermediate or higher.

What you will do:
🔹 Research and develop advanced algorithms in Machine Learning, Neural Networks, Computer Vision, Image & Signal Processing, to be integrated into ASI products;
🔹 Define software specifications and deliver production-ready code that meets project milestones, while addressing constraints such as computational resources, response time, and memory consumption (GPU and CPU);
🔹 Train, optimize, validate and Integrate AI/ML models for diagnostic and imaging applications using Python and its libraries (PyTorch, NumPy, etc);
🔹 Collaborate closely with cross-functional teams, including R&D, Applications, and Product groups;

Interview stages:
🔹 HR Interview;
🔹 Tech interview;
🔹 Client Interviews;
🔹 Reference check;
🔹 Offer;

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.

We are an international developer of IT products for medicine and related services. Our products are used by more than 5,000 doctors and more than 1,000 clinics in Europe.

The goal is to attract the largest possible audience to the main projects - clinics and doctors up to 3 million. As well as expanding unique traffic to 10 million per day until 2025. We are looking for AI Engineer / AI Architect with deep knowledge of Fundamental Mathematics, Probability Theory and Bayesian Statistics, Graph Algorithms, Mathematics of Transformers, Hybrid AI Approaches, Uncertainty Assessment.

Must-have skills are:
1. ML and Data Science (Core):
- Expert in NLP & LLM: Deep understanding of Transformers architecture (BERT, RoBERTa, GPT, T5, Llama/Mistral). Experience with Large Language Models (LLM) – not prompt engineering, but fine-tuning (PEFT, LoRA) of open-source models on specific datasets.
- RAG (Retrieval-Augmented Generation): Experience building RAG systems is required. The AI ​​must be able to search for information in different data sources.
- Named Entity Recognition (NER) & Information Extraction: Ability to extract specific entities from unstructured text.
- Tabular Data & Classic ML: Confident use of classical algorithms (XGBoost, CatBoost, LightGBM) for analyzing structured data and building probability scoring models.
- Frameworks: PyTorch (preferred) or TensorFlow/Keras. Proficiency in HuggingFace, Scikit-learn, Pandas, and NumPy.

2. MLOps:
- Experience wrapping models in APIs (FastAPI, Flask) with minimal latency. 

- Docker knowledge and experience working with local GPU instances are required.
- Experience working with vector databases (Pinecone, Milvus, Qdrant, ChromaDB) for quickly searching for similar cases or working with knowledge bases.

- ML Pipelines: Experience building model training and retraining pipelines (Airflow, MLflow, DVC).

3. MedTech and Security:
- Practical working experience with sensitive personal data and GDPR/DSGVO requirements.

- It is important to be able to deploy and optimize local models (Llama 3, Mistral, Mixtral) within a closed company environment to ensure data privacy.
- Skills in quantization and distillation of models to speed up work without significant loss of quality.

Nice-to-have skills:
- Experience working specifically with medical data (EHR, EMR; HL7, FHIR, ICD-10/11 standards). 

- Knowledge of Interpretability/Explainable AI (XAI) methods. The end user should understand why the AI ​​suggested a particular option (SHAP, LIME).

- Experience with multimodal models.

What we offer:
- Paid holiday for 28 working days.
- Transparent incentive system.

Working with us means:
- Unique technological and innovative projects.
- Gaining experience in modern western world practices in security, scalable architecture, etc.
- In-depth knowledge of telemedicine.
- Working with Big data, high load, distributed computing and data buses.
- Socially important projects.
- Opportunity to influence both technology and product solutions.
- Profitability and stability of a large European company.

About Us

TytoNyx is building an agile AI-powered QMS platform for medical device manufacturers. Our system audits document portfolios against FDA guidance, ISO/IEC standards, cybersecurity expectations, and internal QMS requirements. We already have a functional MVP. We are now hardening the AI layer and backend for reliability, scalability, and production use.

Role Summary

We’re hiring a Senior Software Engineer with strong production GenAI experience to improve the AI core of our regulatory document audit platform. The main focus is AI reliability: RAG, document understanding, evidence extraction, citation grounding, structured outputs, evaluation, and repeatable audit workflows. We need someone who can build production AI systems with solid software engineering practices, clean backend architecture, testing, observability, and AWS deployment.

Responsibilities

• Production GenAI Systems Improve existing AI workflows for regulatory document audits, gap analysis, evidence extraction, compliance reasoning, and report generation. Strengthen RAG pipelines, Improve citation grounding so audit findings link back to source documents, requirements, and supporting evidence. Build AI evaluation and regression testing pipelines for accuracy, completeness, consistency, and failure modes. Work directly with AWS Bedrock, Anthropic Claude, and OpenAI APIs in production.
   
• Regulatory Document Intelligence Improve processing of PDFs, Word documents, spreadsheets, QMS records, cybersecurity files, risk files, design-control documents, and submission artifacts. Build workflows for document classification, metadata extraction, clause mapping, evidence detection, requirement matching, and gap identification.

• Backend & Reliability Harden the existing MVP for production use. Improve API design, data models, background jobs, file-processing workflows, and long-running AI job orchestration. Add retries, timeouts, error handling, job status tracking, logging, and recovery paths. Improve scalability for larger document portfolios and multiple customer audit runs. Write clean, testable, maintainable code with strong code review and CI/CD practices.

• AWS & Production Infrastructure Support AWS-based deployment for AI and backend services. Work with ECS/Fargate or Lambda, RDS/PostgreSQL, S3, SQS, Step Functions, OpenSearch or vector databases, Secrets Manager, KMS, CloudWatch, IAM, and AWS Bedrock. Improve monitoring, alerting, environment separation, secure configuration, and operational documentation.

Required Qualifications

• 5+ years of professional software engineering experience. 2+ years building production GenAI, LLM, RAG, document intelligence, or AI workflow systems.

• Strong Python experience. Experience with FastAPI, Django, Flask, or similar backend frameworks. Strong experience with embeddings, retrieval, structured outputs, prompt orchestration, evaluation, and source-grounded generation. Experience with vector search, semantic search, or document retrieval systems.

• AWS production experience. Solid backend fundamentals: APIs, PostgreSQL, queues, workers, Lambda, object storage, background jobs, and file-processing pipelines. Strong software engineering habits: testing, CI/CD, code review, logging, monitoring, documentation, and maintainable architecture.

About TytoNyx Inc.

TytoNyx is a young, dynamic startup poised to disrupt the medical device manufacturing sector with an amazing idea whose sky's-the-limit potential is limitless. Our innovative spirit fuels our cloud-based platform, which leverages advanced AI to streamline and improve quality management processes. We’re dedicated to positively transforming healthcare outcomes as a team of enthusiastic pioneers.

ABOUT THE COMPANY
AI startup building digital employees (AI agents) that handle real business operations — not another ChatGPT wrapper. Our architecture: a modular monolith (uv workspaces + Turborepo) that cleanly extracts into microservices once product-market fit is reached.

RESPONSIBILITIES
— Rapid MVP development of AI agents
— Building and maintaining agent graphs with LangGraph
— Background task orchestration (Temporal — upcoming)
— Enforcing strict modularity within the monorepo
— Working with LLMs and vector databases

MUST-HAVE
— Senior Python / Backend engineer
— Strong FastAPI and PostgreSQL skills
— Solid understanding of modular architecture
— Hands-on experience building multi-agent systems with LangGraph

NICE-TO-HAVE
— Product thinking
— React / Next.js
— Temporal (orchestration)
— Vector DBs: Qdrant, pgvector
— FinOps/LLMOps: LiteLLM, Traceloop
— Evals: Ragas
— Vercel AI SDK

OFFER
— Fully remote
— No bureaucracy, fast processes
— Strong team, rapid growth

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed.

Now we are looking for a Software Development Engineer (MLOps) to join us as part of our team.

About the role

As a Senior ML Operations Engineer, you will support teams building and deploying AI-driven solutions, helping them overcome common challenges in the ML development, deployment, and support lifecycle. This role offers autonomy in decision-making, encouraging a proactive approach to solving complex issues and finding optimal solutions for scalable systems.

About the project

PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials and many more.

Team composition

1 Engineering Manager, 4 Senior ML Ops Engineers

Work Environment

The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology.

As a qualified expert, You will

• Serve as a force multiplier for development teams by creating golden paths that remove roadblocks and improve ideation and innovation.
• Collaborate with other engineers, product managers, and internal stakeholders in an Agile environment.
• Provide mentorship, technical guidance, and perform code reviews for team members.
• Design and deliver on projects end-to-end with little to no guidance.
• Provide support to teams building and deploying AI applications by addressing common pain points in the MLDLC.
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities.
• Support the vision and values of the company through role modeling and encouraging desired behaviors.
• Participate in various cross-functional company initiatives and projects as requested.
• Contribute to strategic planning in a way that ensures the team is building exceptional products that bring real business value.
• Evaluate frameworks, vendors, and tools that can be used to optimize processes and costs with minimal guidance.

We’re looking for you if you have

• Degree in Computer Science, Information Systems, Machine Learning, or a similar field preferred (or equivalent practical experience).
• 5+ years of hands-on software development experience with Python (Java experience with strong Python proficiency also considered).
• 4+ years of experience designing and building distributed software systems and architectures.
• 3+ years of hands-on experience deploying and operating Machine Learning services in production.
• Experience supporting ML lifecycle operations including post-deployment monitoring and maintenance.
• Experience in cloud-native stack, with a practical understanding of containerization technologies such as Kubernetes and Docker.
• Demonstrated experience with SQL and NoSQL database design and implementation.
• Ability to decompose complex problems into iterative, well-defined solutions.
• Strong problem-solving abilities with focus on building scalable, efficient, and maintainable systems.
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions.
• Ability to be a team player who can also work independently.
• Experience working across multiple development teams is a plus.

Desired Skills

• Experience with cloud platforms (AWS, Google Cloud Platform, or Azure).
• Proficiency in GitOps practices and CI/CD pipeline development and management.
• Observability and monitoring: Integration experience with observability tools (Prometheus, Grafana) and building instrumented, production-ready systems.
• LLM Infrastructure: Experience provisioning and managing Large Language Models through managed services (Azure OpenAI, Google Vertex AI, Amazon Bedrock).
• LLM Tooling: Hands-on experience with LLM gateways (LiteLLM) and agentic frameworks (LangGraph, LangSmith, or similar).
• Vector Systems: Practical experience with vector embedding models and vector databases (Pinecone, Weaviate, Milvus, pgvector).
• RAG Systems: Experience building Retrieval-Augmented Generation systems and evaluating both retrieval quality and generation performance.
• Cloud-native experience with services like Amazon SageMaker, Google Vertex AI, or Azure ML
• Familiarity with ML frameworks and tools: PyTorch, TensorFlow, scikit-learn
• Experience with data infrastructure: Redis, Elasticsearch, Apache Kafka.
• ML experiment tracking and model management: Weights & Biases, MLflow, KubeFlow.
• API development with FastAPI or similar frameworks.
• Java programming experience is a plus.

Interview Process

1. Pre-Screening with the recruiter
2. Tech Interview(ML Fundamentals, Software Engineering) + Live Coding (up to 1,5 hours)
3. ML System Design Interview (up to 60 min)
4. Interview with Engineering Manager (60 min)
5. Final Client Interview (60 min)

Role in one line

Build the agent runtime — the brains of the platform: stateful LangGraph workflows, RAG, tool integrations, model routing, human-in-the-loop gates, and audit-grade logging — in Python.

Context

We are building a multi-agent AI platform for a regulated banking client. The agent runtime is a Python / FastAPIservice exposing OpenAI-compatible endpoints, with agents implemented as LangGraph graphs and tools exposed over MCP. Sensitive workloads (KYC, PII) run on self-hosted open-weight models on EU infrastructure (Hetzner); less sensitive workloads route to frontier models via AWS Bedrock EU. The AI engineer owns the agent logic, retrieval, and the model / tool layer.

What you will work on

• Design and build stateful agent graphs in LangGraph — multi-stage workflows, tool calling, and interrupt-based human-in-the-loop gates (e.g. the six-stage KYC assistant).
• Build RAG pipelines: ingestion, chunking, embeddings, retrieval, and grounded Q&A with source citations (e.g. meeting analysis, search lens).
• Implement structured-output patterns where the LLM emits validated JSON only and deterministic engines do the rest — keeping the model out of the render path for document generation.
• Integrate tools over MCP (streamable-http) and wire agents to bank data sources behind the tool layer.
• Work across hosted and self-hosted models — a per-task model router selecting between Bedrock EU and on-prem open-weight models — with prompt design, evaluation, and cost / latency awareness.
• Build audit-grade logging and provenance for every AI operation, with PII handled by hashing rather than plaintext.

Must-have

• Strong Python: production-grade, typed, tested — not notebook-only.
• LangChain and LangGraph: hands-on building stateful graphs, tool / function calling, and human-in-the-loop interrupts.
• LLM application patterns: RAG, prompt design, structured output / JSON-schema validation, and evaluation of agent behaviour.
• Retrieval stack: vector stores (pgvector and / or Qdrant) and embeddings.
• Serving: FastAPI for agent endpoints; comfort with async Python.
• Model access: working with hosted APIs (AWS Bedrock) and self-hosted open-weight models (Llama, Mistral, Qwen).

Nice-to-have

• Banking / regulated experience; awareness of audit logging, PII handling, and EU data residency.
• MCP (Model Context Protocol) tool integration.
• ASR / speech-to-text pipelines (for meeting analysis).
• MLOps for self-hosted inference (vLLM, Ollama, or similar) on EU infrastructure (Hetzner).
• Workflow orchestration (e.g. Camunda) and deterministic document rendering (docxtpl, openpyxl).

Tech stack you will touch

Python, LangChain, LangGraph, FastAPI · pgvector / Qdrant, embeddings · AWS Bedrock EU and self-hosted open-weight LLMs on Hetzner · MCP servers (streamable-http) · Docker, Git, CI/CD.

Ways of working

• Remote, distributed delivery team; English working language; scrum-light cadence.
• Banking-grade rigor: every AI operation logged and auditable, human-in-the-loop by design, compliance built into the architecture — not bolted on.
• Agents prepare, retrieve, draft, and propose; the trigger and the final action always stay with a human.

Important
As this is a Germany-based project, we are primarily seeking candidates based in Western Ukraine, with Vinnytsia and Lviv being our preferred locations.

We’re Expanding and Looking for Talented Developers!

You’ll work directly with our technical founder (experienced developer with a strong AI interest), helping shape our AI direction from the ground up.

The main focus is prompt engineering, the ability to build pipelines for AI agents, and working with memory and external data.

Our team specializes in working with startups, starting from the earliest stages of their development. Each project we take on is a unique challenge, requiring innovative and effective solutions. That’s why we always stay at the cutting edge of technology.

We believe that productive work is only possible in a comfortable environment with excellent planning. The best solutions are built on well-thought-out architecture, quality code, and modern technologies.

If these priorities resonate with you, you’ll love being part of our team!

Requirements

• 1+ years of experience with LLM APIs (e.g., OpenAI, Hugging Face Inference API).
• Understanding of how pretrained models work (LLMs, image-to-text, TTS/STT).
• 1+ years of experience building simple pipelines in Python using libraries like Transformers, Diffusers, Gradio, LangChain, or similar.
• 1+ years of experience with visual AI tools (ComfyUI, Automatic1111, or similar).
• Understanding of REST APIs and integrating ML features into web services (via API requests).

• Ability to work with texts: translations, basic transformations (tokenization, embeddings, chunking, etc.).

   

Nice-to-Haves

• 1+ years of experience with or interest in RAG (Retrieval-Augmented Generation).
• Basic fine-tuning skills or familiarity with LoRA / DreamBooth.
• 1+ years of experience building simple chatbots or AI agents.
• Exposure to multimodal tasks (text → image / audio / video).
• Prompt engineering knowledge to control LLM behavior.

• 1+ years of experience preparing glossaries or structured files to support translation tasks.

   

Responsibilities

• Help build and maintain simple AI pipelines for use in our internal tools and client web services.
• Integrate LLM and multimodal models (image, video, audio) into production-ready features.
• You’ll work directly with our technical founder (experienced developer with a strong AI interest), helping shape our AI direction from the ground up.
• Collaborate with backend/frontend engineers to deliver AI-driven features. Prepare and use glossaries, structured data, and RAG files for translation and document understanding tasks.
• Build early versions of AI-powered chatbots, assistants, and user-facing agents.

• Use both Python and visual tools (e.g., ComfyUI) for building and debugging pipelines. Take initiative and learn new tools or techniques as needed — you’ll be our first AI specialist.

   

Additionally:

• DevOps support is available in the team to help with deployment and running models locally.

• Complex integrations or tuning tasks can be delegated internally if needed.

   

What We Offer

• Possibility to be a part of startups from around the world
• Supportive, understanding, and flexible management
• Paid vacations and sick leave
• A friendly and welcoming team

BigD is seeking a talented AI multi-agent engineer (n8n) to join our dynamic team. 

BigD is an iGaming operator focused on the LATAM (top brand). But that’s not all — we also have a thriving Affiliate Program, a handy Payment solution, and an AI user acquisition solution. We are a big family of over 500+ creative minds.
 

What to do:
- n8n Workflow Development & Optimization: Design, configure, and maintain robust automation workflows within the n8n platform, ensuring high system uptime and performance.
- AI-Driven Data Analysis: Integrate AI solutions for intelligent data analysis, text categorization, and structured information extraction from unstructured sources.
- Process Automation with AI: Build and deploy AI agents and assistants to automate repetitive, routine operational tasks across different business units.
- Content Generation & Automated Publishing: Create automated pipelines for generating digital content (text and visuals) using generative AI and orchestrate automated publishing to external platforms and social media.
- LLM Integration & Prompt Engineering: Work with state-of-the-art AI models (OpenAI, Anthropic, Gemini) via API, focus on prompt tuning, and design reliable model-interaction logic.
- Business Process Improvement & Cost Reduction: Proactively analyze existing workflows to identify inefficiencies, propose AI-driven optimizations, and implement solutions to reduce operational overhead.

We are looking for:

- Self-hosted n8n & Scaling: Experience deploying and scaling self-hosted n8n instances using Docker, PostgreSQL, and Redis (Queue Mode).
- n8n Custom Nodes: Hands-on experience developing custom n8n nodes using TypeScript.
LLMOps & Monitoring: Familiarity with LLM evaluation and observability tools (e.g., Langfuse, LangSmith, Phoenix).
- Advanced RAG: Experience with hybrid search, reranking strategies, and metadata filtering.
- Human-in-the-Loop (HITL): Track record of designing approval-based workflows where agents pause for human intervention.
- Alternative Agent Frameworks: Familiarity with code-first agent platforms like CrewAI, AutoGen, or LangGraph.
- Local LLMs: Experience integrating or hosting open-source models via Ollama or vLLM.

Who Thrives in This Role:

Proactive and solutions-oriented — you’re not afraid to suggest new ideas and take ownership.
Able to explain technical concepts clearly and simply.
Detail-oriented — you thoroughly test your automations and care about quality.
Independent and good at managing your own workload.
Eager to learn and stay current with new technologies.

Working conditions:

• Direct communication with the core TEAM
• 28 calendar days of vacation
• Paid sick leave
• Sports compensation
• Compensation for courses and training
• Day off for birthday
• Flexible work schedule
• Regular salary reviews
• Salary paid at a favorable rate
• Non-toxic work environment, free of bureaucracy

• Stable salary payment

   

Join a fast-growing team at the forefront of the iGaming industry, where your expertise will directly contribute to the company's growth and success.

We are looking for a Middle AI Engineer who will help us build, integrate, and scale AI-powered products that solve real business challenges.

This role is focused on creating production-ready AI solutions — from backend services and LLM integrations to RAG systems, AI agents, and workflow automation. You will work closely with Product Managers, developers, and business teams to transform ideas into reliable AI products that deliver measurable value.

What you will do:

• Develop production-ready AI services, backend components, APIs, and integrations for internal and external AI products.
• Design and implement AI solutions based on Large Language Models (LLMs), RAG architectures, AI agents, and workflow automation.
• Build and optimize Python-based services and backend infrastructure with a focus on scalability, reliability, and maintainability.
• Integrate and work with different types of AI models — including proprietary APIs (OpenAI, Anthropic, Gemini, etc.) and locally hosted models.
• Design and improve RAG pipelines: data processing, embeddings, vector search, retrieval optimization, knowledge bases, and AI response quality improvement.
• Develop AI agent systems and automation workflows, including integrations with external APIs, corporate systems, and internal tools.
• Conduct technical experiments with models, prompts, architectures, and inference parameters to identify the most effective solutions.
• Implement AI quality evaluation and monitoring approaches: analyze model performance, improve reliability, reduce errors, and optimize system efficiency.
• Collaborate with Product Managers and cross-functional teams to translate product requirements into technical solutions and scalable architectures.

• Ensure AI services are secure, stable, and production-ready by monitoring performance, resolving issues, and continuously improving systems.

   

What we expect from you

• 3+ years of commercial software development experience with strong Python expertise.
• Experience building backend services, APIs, and integrations using modern technologies.
• Strong understanding of software engineering principles: clean code, architecture patterns, testing, scalability, and maintainable solutions.
• Practical experience developing AI products based on Large Language Models (LLMs).
• Hands-on experience with RAG systems, embeddings, vector databases, retrieval optimization, and AI application development.
• Experience working with AI model integrations, including external APIs and/or locally deployed models.
• Understanding of AI agents, workflow automation, and approaches to building reliable AI systems.
• Experience with Docker, CI/CD, and production deployment processes.
• Ability to analyze AI system performance and improve quality, efficiency, and reliability.
• Upper-Intermediate English level (B2+) 

Will be a plus:

• Experience with fine-tuning or adapting AI models.
• Experience with MLOps / LLMOps practices.
• Knowledge of NLP approaches.
• Experience with cloud platforms and scalable infrastructure.

What we offer

• Competitive compensation up to $4,000, depending on your experience and expertise.
• Office-based work in Lviv with the possibility of a hybrid schedule.
• High level of technical ownership and the opportunity to solve challenging engineering problems.
• Professional development opportunities: company-sponsored courses, training, and access to necessary tools and resources.
• A team of experienced specialists who value expertise, initiative, and high-quality engineering.
• The opportunity to become one of the key engineers shaping the company’s AI direction.
• Relocation support for candidates from other cities, including assistance with moving and adaptation in Lviv.