We're hiring a Senior AI Engineer who enjoys owning the entire development lifecycle. From shaping the architecture to building and deploying solutions, you'll use AI tools every day to work smarter and faster. You'll lead projects with minimal oversight, guide other engineers when needed, and confidently deliver independently while collaborating with experts for reviews and validation. Our team builds enterprise-grade AI applications, including RAG systems, agentic workflows, and modern AI-powered solutions.
What you'll do:
- Work directly with clients: translate business problems into AI solutions, explain how the technology behaves (and its limits), and report progress clearly;
- Support proposals and pre-sales for new AI engagements;
- Lead AI engineers on engagements: if needed to have ability to set tasks, review work, give feedback, and support growth and performance;
- Own delivery quality and the path from PoC to production;
- Design end-to-end AI-powered experiences and the systems behind them: model selection, deployment patterns, infrastructure;
- Architect and build RAG pipelines - chunking (semantic/recursive/hierarchical), embedding selection, retrieval, hybrid search, re-ranking, and evaluation;
- Build agentic / multi-step workflows (LangChain, LangGraph, or equivalent): multi-agent designs, agent-to-agent protocols, and tool/API/MCP-style integration with enterprise systems;
- Deploy on a hyperscaler AI platform (Azure AI Foundry, AWS Bedrock, Google Vertex AI, K8s based or equivalent);
- Build for production: observability, evaluations, AI safety, bias/failure-mode handling, security, and cost control;
- Write the production code yourself - hands-on;
- Use AI development tools (GitHub Copilot, Cursor, Claude Code, etc.) as part of how you build and validate what they produce.
Who are you:
- 5+ years in software/AI engineering, with substantial hands-on delivery of production AI/LLM systems (not only PoCs or notebooks);
- Deep RAG expertise: chunking strategies, embedding models, vector databases, retrieval, re-ranking, and evaluation frameworks;
- Strong with agentic / multi-step LLM workflows and orchestration (LangChain, LangGraph, or equivalent) and tool/API integration;
- Able to build real software — production-grade code in at least one of Python, .NET / C#, Java, or Node.js / TypeScript (APIs, services, integrations);
- Experience deploying AI workloads on at least one hyperscaler AI platform;
- Solid on production concerns: observability, evaluation, safety, security, cost;
- Daily, fluent use of AI development tools in your own work;
- Proven ability to take an AI solution from idea to production independently;
- Confident client-facing and team communication;
- Knowledge graphs and graph-based retrieval (Neo4j, RDF/SPARQL, GraphRAG);
- NL2SQL, semantic layers, intelligent document processing;
- LLMOps / MLOps tooling and practices.
Nice to have:
- Broad / multi-stack traditional software-engineering background;
- Experience with large, regulated organisations (banks, insurers, government, utilities);
- Relevant certifications;
- Formal team-leadership / performance-management experience.
We appreciate the interest of all applicants. Please note that only those whose qualifications align closely with the position requirements will be contacted for the next steps in the selection process.
All applications will be handled with confidentiality.
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