Summary:

We are looking for a Senior Full Stack Engineer with a strong foundation in backend development and DevOps tooling, and working knowledge of frontend technologies like React or Angular. In this role, you will build scalable APIs using Python and/or .NET, contribute to integrating AI workflows, and support deployment through modern CI/CD pipelines. You’ll also enhance frontend components as needed to connect APIs and deliver end-to-end functionality. This is a high-impact role for someone who enjoys working across the stack, with a primary focus on backend systems and infrastructure automation.

WHAT YOU'LL DO

• Design and implement backend APIs using Python (FastAPI or similar) and .NET (C#) where applicable
• Build and extend LLM wrappers, prompt routers, and AI orchestration logic
• Integrate backend services with vector databases, embedding pipelines, and RAG workflows
• Manage deployments using Azure DevOps, Docker, and Kubernetes (K8s)
• Configure and maintain Helm charts, environments, and containerized services
• Collaborate with frontend, AI, and QA engineers to ship production-ready features
• Maintain logging, observability, and API-level telemetry for AI service health
• Participate in designing proof-of-concept (POC) experiments using new AI APIs or retrieval methods

WHO YOU ARE

• Bachelor’s degree in Engineering, Computer Science, or a related technical field
• 5+ years of experience in backend software engineering or full stack development
• Proficient with programming in Python and .NET (C#) for API development
• Solid experience with RESTful API design, service integration, and microservice patterns
• Exposure to React or Angular — enough to support frontend integration, make enhancements, and debug UI flows as needed
• Proficient with SQL and NoSQL databases
• Experienced with CI/CD pipelines, preferably using Azure DevOps
• Experience deploying applications using Kubernetes (K8s), Helm, and Docker
• Proficient with Git and basic DevOps/config management practices
• Familiarity with vector databases (e.g., ChromaDB), embeddings, and RAG-based systems

Nice to Have

• Exposure to LLM APIs such as OpenAI, Anthropic, or Azure OpenAI
• Familiarity with tracing tools, error monitoring, or rate limiting for AI infrastructure
• Contributions to POCs or prototypes in AI/ML or conversational platforms
• Understanding of prompt lifecycle, token limits, and performance trade-offs

What You’ll Learn & Gain

• Deep experience building scalable infrastructure for LLM-powered AI systems
• Ownership of backend logic driving Copilot, search, and workflow-based AI interactions
• Opportunity to scale RAG and vector-based systems from POC to production
• A collaborative team that empowers experimentation, innovation, and technical ownership

This role presents an exciting opportunity to design and deliver the backend foundation for AI-enhanced enterprise platforms. If you're driven to combine engineering precision with AI innovation, we encourage you to apply.