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 AI Engineer (or equivalent) with a strong focus on Gen AI implementation; 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.
EU work permit is required

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
Specialization in GenAI and adjacent areas, with strong support for continuous learning and obtaining internationally recognized certificates.
Hybrid way of work in a modern Prague office.
International environment where personal development and growth are supported and highly encouraged.
Unique opportunity for a long‑term career and promotions within Deloitte.
Attractive and competitive salary, including a wide range of fringe benefits:
Annual performance bonus rewarding excellence and dedication.
Flexible benefits package via cafeteria system (meals, pension, sports, culture, and more).
Extra time off, including additional vacation and sick days.
Health, travel and life insurance to support your wellbeing and peace of mind.
Support during important life events, such as illness or parental leave.
Professional development through internal and external trainings, cloud partner certifications and mentoring.
Access to sports, wellbeing and social activities, plus a friendly, inclusive team culture.

Also:

✨ Professional Growth – Continuous learning with access to trainings (Azure, GCP, AWS, Databricks), free certifications vouchers and business udemy.com subscription, 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.

General Information

Position

GenAI Engineer | Prague

Work arrangement

Full-time

City

Prague

Country

Czech Republic

Department

Consulting

Team

Engineering, AI & Data

Area of interest

AI - Artificial Intelligence, Cloud, Consulting, Data & Analytics, Engineering

Way of work

Hybrid

GenAI Engineer | Prague

About the role

Skills

Benefits

Perks

Full job details

Description & Requirements

General Information