Senior MLOps Technical Lead

Job Summary

The team is seeking an AI/ML Engineer to build and operationalize AI solutions across RAG, agentic workflows, knowledge graphs, and machine learning. The role is hands-on and spans experimentation, backend development, deployment, evaluation, and production support.

Key Responsibilities

· Design and build RAG and agentic AI solutions from prototype through production

· Develop AI workflows using Python, LangGraph, LangChain, or comparable frameworks

· Build backend services and APIs using FastAPI, REST APIs, and containerized deployment patterns

· Develop retrieval pipelines covering ingestion, embeddings, indexing, retrieval, reranking, grounding, and citations

· Support GraphRAG and knowledge graph use cases that combine structured and unstructured information

· Build and maintain data and AI pipelines using Databricks

· Integrate AI applications with Azure and enterprise services, including identity, security, logging, and monitoring

· Evaluate solution quality using retrieval metrics, RAG evaluations, LLM-based evaluation, and human review

· Collaborate with engineers, architects, product teams, and domain specialists to move use cases into production

· Support technical documentation, troubleshooting, optimization, and post-production improvements

Skill Requirements

3+ years of relevant software, data, machine learning, or AI engineering experience

· Strong programming capability in Python and experience building production APIs or backend services

· Hands-on experience with RAG, LLM applications, or agentic AI workflows

· Experience with FastAPI, REST APIs, Docker, Azure DevOps Git, and CI/CD

· Experience with Microsoft Azure and cloud-based application deployment

· Familiarity with Databricks, data pipelines, SQL, and common Python data/ML libraries

· Understanding of authentication, authorization, RBAC, secrets management, logging, and monitoring

· Experience evaluating AI systems through retrieval metrics, RAGAS or similar frameworks, or task-specific benchmarks

· Strong communication and collaboration skills across technical and non-technical teams

· Ability to take ownership and work iteratively from experimentation to secure, maintainable production solutions

Other Requirements

Experience with GraphRAG, knowledge graphs, ontologies, graph databases, Azure AI services, MCP, or enterprise technology environments.