Develop new GenAI applications for a European client. Design and implement end-to-end Generative AI solutions using Python. Collaborate with DevOps / LLMOps teams for deployment, monitoring, scaling, and cost optimization.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
SNI is serving as a trusted IT Outsourcing partner in line with the needs of World's most prestigious firms and carried out successful projects worldwide.
For one of our European clients, we are currently looking for a Senior LLM Engineer to develop new GenAI applications.
Details:
- Start date: ASAP
- Duration: 6 months with extension
- Work model: Fully remote within EU countries
Scope:
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- Design and implement end-to-end Generative AI solutions using Python
- Build agentic AI systems and workflows using frameworks such as LangGraph, tool/function calling, MCP, and multi-agent orchestration
- Develop advanced RAG pipelines (ingestion, chunking, embeddings, vector search, re-ranking, grounding validation)
- Implement memory architectures (short-term, long-term, summarised, and vector-based memory)
- Integrate, evaluate, and optimize multiple LLMs (e.g., GPT-4.x, GPT-4o)
- Build structured output and tool-calling systems with schema validation
- Design evaluation frameworks for hallucination detection, quality scoring, latency, and cost efficiency
- Implement Responsible AI guardrails, including input/output filtering and fallback mechanisms
- Collaborate with DevOps / LLMOps teams for deployment, monitoring, scaling, and cost optimization
Skills:
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- Strong hands-on Python development (mandatory)
- Experience with GenAI frameworks such as LangChain, LangGraph, and CrewAI
- Deep understanding of agentic AI systems, orchestration, and tool integration
- Experience with Azure AI Foundry and Azure OpenAI Service
- Familiarity with vector databases (Azure AI Search, Pinecone, Weaviate, OpenSearch)
- Understanding of tokenization, context windows, rate limits, and LLM cost optimization
- Experience with API integration, asynchronous programming, and resilient system design
- Strong knowledge of Responsible AI principles and risk mitigation techniques
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