AI / LLM Engineer

• *Job Description:**
• -------------------

• As an AI LLM Engineer you will build the AI enabled capabilities that support summaries narratives explanations recommendations retrieval evaluation and governed human review experiences across an enterprise platform
• You will work closely with architects product teams data engineers backend engineers security QA and domain specialists to convert AI patterns into production ready software components

• *Key Responsibilities:**
• ------------------------

• Design and implement LLM powered workflows for summarization narrative generation classification extraction contextual reasoning explanation and reviewer assist use cases
• Build retrieval augmented generation pipelines including document ingestion chunking embedding generation metadata tagging vector indexing retrieval tuning and grounded response generation
• Develop reusable prompt templates prompt versions context builders response schemas evaluation routines and AI orchestration services
• Integrate with enterprise AI services such as Azure OpenAI Azure AI Foundry OpenAI APIs Google Gemini Anthropic Hugging Face or equivalent approved platforms
• Implement AI run logging prompt model metadata capture evidence citations output traceability reviewer feedback capture and human in the loop controls
• Build AI evaluation routines for answer quality retrieval quality hallucination checks regression testing consistency and groundedness
• Collaborate with backend and DevOps teams to containerize AI services deploy them securely monitor usage track costs and troubleshoot production issues
• Support responsible AI practices such as prompt injection checks data leakage prevention policy based guardrails and AI output validation

• *Technical Requirements:**
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• Minimum 10 years of experience in software engineering AI ML engineering applied ML data science engineering or related roles
• Strong hands on Python programming experience and practical exposure to LLM based application development
• Experience with RAG vector databases embeddings prompt engineering evaluation frameworks and AI service integration
• Experience with frameworks such as LangChain LangGraph LlamaIndex Semantic Kernel AutoGen CrewAI or equivalent tools
• Working knowledge of REST APIs microservices SQL structured data concepts Git workflows testing and software engineering practices
• Understanding of document extraction semantic search NLP retrieval quality hallucination risk prompt safety and AI evaluation methods
• Ability to build production oriented AI components rather than isolated proof of concept demos

• *Additional Responsibilities:**
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• Experience with Azure OpenAI Azure AI Foundry Azure AI Search Azure Document Intelligence Google AI Studio Gemini AWS Bedrock or Vertex AI
• Exposure to RAG evaluation tools such as RAGAS DeepEval Promptfoo LangSmith or equivalent frameworks
• Experience with AI governance prompt model registry AI audit logs explainability groundedness checks and human review workflows

• *Preferred Skills:**
• --------------------

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