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:

Minimum 7 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:

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:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->traditional ai ml,Technology->AI-AI Engineering->LLMOps,Technology->AI-Data science->Amazon ML,Technology->AI-Data science->PYTHON,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag),Technology->Cloud Platform->Azure Networking Services-> Azure Bastion,Technology->Enterprise Architecture->API / Microservices Architecture,Technology->Enterprise Architecture->Digital Architecture