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Senior AI Engineer

About the Role

We are looking for a Senior AI Engineer to design and build production-grade LLM and agentic applications on Microsoft Azure. You will work across AI architecture, backend engineering, data platforms, and deployment to deliver scalable, reliable solutions.

Key Responsibilities

• Design and develop LLM-powered applications and agentic workflows.

• Build multi-step agents using LangGraph and LangChain.

• Apply agentic design patterns, tool calling, planning, routing, and reflection.

• Design and implement short-term and long-term memory systems for AI agents.

• Develop scalable APIs and services using Python and FastAPI.

• Build and optimize retrieval-augmented generation (RAG) pipelines.

• Integrate vector databases such as Redis and PostgreSQL with pgvector.

• Work with Databricks for data processing, experimentation, and production workflows.

• Containerize and deploy services using Docker on Microsoft Azure.

• Integrate external systems, tools, and enterprise APIs.

• Monitor, evaluate, and improve AI system quality, latency, cost, and reliability.

• Collaborate with product, data, and engineering teams to deliver robust AI solutions.

Required Skills

• Strong professional experience with Python.

• Hands-on experience building LLM applications and AI agents.

• Expertise with LangChain and LangGraph.

• Experience with FastAPI and RESTful API development.

• Strong understanding of agentic design patterns and workflow orchestration.

• Experience implementing memory and state management for AI agents.

• Experience with RAG, embeddings, semantic search, and prompt engineering.

• Experience with Redis and/or PostgreSQL with pgvector.

• Proficiency with Docker and containerized deployments.

• Experience working with Databricks and modern data platforms.

• Experience developing and deploying solutions on Microsoft Azure.

• Understanding of LLM evaluation, observability, and production best practices.

• Strong software engineering, debugging, and system design skills.

Nice to Have

• Experience with Azure OpenAI Service or other Azure AI services.

• Familiarity with Azure Machine Learning, Azure Container Apps, AKS, or Azure Functions.

• Experience with MLflow, CI/CD, and cloud-based monitoring.

• Experience building secure, enterprise-grade AI systems.

• Knowledge of structured outputs, function calling, and model routing.

What Success Looks Like

• Reliable AI agents deployed in production on Azure.

• Well-designed, maintainable, and scalable AI services.

• Improved response quality, system performance, and user experience.

• Strong engineering practices across testing, monitoring, security, and deployment.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of software engineering experience, including significant experience in AI/ML or LLM application development.

• Strong communication, ownership, and problem-solving skills.