We're looking for a hands-on Senior AI Engineer to build and deploy production-grade generative AI solutions. This role focuses on taking use cases from concept to production, working closely with product, business, and engineering teams.
This is not a research role-candidates must have real experience building and deploying LLM-based systems in production.
Key Responsibilities
Build backend services and APIs for AI-driven applications
Develop and integrate LLM solutions (Azure OpenAI / AI Foundry)
Design RAG pipelines (embeddings, vector search, retrieval systems)
Deploy scalable applications using Docker and Kubernetes (AKS)
Translate business use cases into production-ready solutions
Optimize performance, cost, and reliability of AI systems
Support monitoring and observability of deployed solutions
Contribute to agentic workflows and orchestration patterns
Required Skills
Strong Python (APIs, async, production systems)
Hands-on with LLMs/GenAI (Azure OpenAI, LangChain, Semantic Kernel)
Experience with RAG, embeddings, and vector databases
API frameworks (FastAPI or similar)
Docker + Kubernetes (AKS preferred)
Azure or similar cloud experience
Strong system design and production deployment experience
Nice to Have
Azure AI Search, Pinecone, or similar
Agentic AI / orchestration frameworks
React/TypeScript (basic UI work)
CI/CD and DevOps exposure
What We're Looking For
Proven experience shipping AI solutions (not just experimentation)
Ownership from prototype → production
Ability to work in fast-paced, client-driven environments
Strong communication across technical and business teams