LLM Engineer

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.

Scope:

• 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:

• 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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