GenAI Engineer | Prague - - 19345

General Information

Position

GenAI Engineer | Prague

Work arrangement

Plný úväzok

City

Praha

Country

Česká republika

Department

Consulting

Team

Engineering, AI & Data

Area of interest

Cloud, Consulting, Data & Analytics, Engineering

Way of work

Čiastočná práca z domu

Description & Requirements

Who we are looking for

🎯We’re building agentic systems that do real work in production: tool-using workflows, RAG, structured outputs, guardrails, and measurable quality. If you like shipping and iterating fast - but still care about doing it properly - this is the team.

You’ll work with Solution Architects and LLMOps, but your focus is simple: build the thing, make it reliable, and keep improving it.

🔎What you bring:

2+ years as a GenAI Engineer; ideally some NLP background for RAG and Talk2Document work.
Python-first engineer who can build production APIs/services (FastAPI or similar).
You’ve built agentic systems with LangGraph / LangChain / PydanticAI / CrewAI (or similar).
You’re comfortable integrating tools/data safely (timeouts, retries, idempotency, rate limiting).
You’ve worked with RAG/vector search (Azure AI Search, Pinecone, Redis Vector, Milvus/Chroma).
You’ve shipped Talk2Data and/or Talk2Document-style solutions (or very similar patterns).
You care about quality: eval harnesses + regression suites, and you can use LangSmith/Langfuse/Datadog to debug what’s happening.
Familiar with MCP and secure model-to-tool/data connectivity.
Bonus: A2A patterns / agent-to-agent coordination.
Bonus: agent builder frameworks (Azure AI Foundry, AWS Bedrock Agents, Vertex AI Agent Builder, or similar).
Cloud experience: Azure preferred, AWS/GCP fine.

Your future role

🚀What you will build:

Agent workflows with LangGraph / LangChain / PydanticAI / CrewAI (routing, retries, fallbacks, timeouts, human-in-the-loop).
Tool calling that doesn’t break: APIs, databases, and internal services with clean contracts, predictable behavior, and safe error handling (retries/timeouts, idempotency, rate limiting).
Hybrid systems: pre-built agents plus a thin custom orchestration layer (interfaces, policies, guardrails, reuse).
MCP integrations: implement MCP servers/clients so models can safely access tools/data (DBs/APIs/files) using least-privilege patterns and audit-friendly logging.
RAG + knowledge systems: chunking, embeddings, indexing, retrieval strategies, grounding patterns; vector stacks like Azure AI Search, Pinecone, Redis Vector, Milvus/Chroma; doc ingestion with Azure Document Intelligence.

Real use cases:

Talk2Data (safe querying + interpretation of enterprise data)
Talk2Document (Q&A/summarize/extract/reason over docs with citations/grounding)
Evaluation + observability: automated evals (task success, groundedness/relevance, safety, latency, cost), regression suites, and run tracing for debugging using LangSmith / Langfuse / Datadog.
Cloud GenAI: Azure OpenAI / Azure AI Foundry + Azure AI Search / Document Intelligence / Content Safety. AWS/GCP equivalents welcome (Bedrock/Vertex AI + search/document pipelines).

What we offer

A global network + a strong regional AI&D community (~160 people).
A dedicated technical team that’s actively growing and open to experimenting with new tech (when it actually helps).
Consultancy work, but on real problems with real impact - solutions people use.

Also:

✨ Professional Growth – Continuous learning with access to SAP trainings, certifications, and mentorship.

💰 Attractive Package – Competitive salary, performance bonuses, meal vouchers, extra vacation days, and flexible benefits.

🌍 International Projects – Work with leading companies across Europe and beyond.

📈Career Development – Clear paths for advancement into senior consultant and manager roles.

🏢 Modern Workplace in Prague – Hybrid working model with a centrally located office.

🎉 Culture & Community – Friendly, diverse teams, team-building events, and supportive leadership.

#LI-NF1