Senior AI Engineer

Job description

Dreaming big is in our DNA. It’s who we are as a company. It’s our culture. It’s our heritage. And more than ever, it’s our future. A future where we’re always looking forward. Always serving up new ways to meet life’s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential.

The power we create together – when we combine your strengths with ours – is unstoppable. Are you ready to join a team that dreams as big as you do? 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 LangFuse, 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.