Job Summary
We are seeking a strong Full Stack AI Engineer with practical AI experience and solid software engineering capabilities. The role emphasizes engineering ability, technical judgment, and hands-on development experience. The ideal candidate will be capable of building and owning features across APIs, frontend applications, databases, testing, troubleshooting, and deployment while integrating AI capabilities into software solutions.
Key Responsibilities
• Develop and maintain full-stack applications across APIs, frontend interfaces, databases, testing, and troubleshooting.
• Build backend services and APIs using Python.
• Develop frontend applications using React, TypeScript, or other modern frontend frameworks.
• Apply Claude Code, Codex, or similar agentic coding tools in software development workflows.
• Build and integrate AI-powered solutions using Large Language Models (LLMs), prompting techniques, structured outputs, tool calling, and Retrieval-Augmented Generation (RAG).
• Implement AI evaluation and observability practices, including runtime validation, telemetry, troubleshooting, and measurement of AI quality.
• Work with Azure and/or Google Cloud Platform (GCP) environments.
• Implement application development and deployment workflows using Docker, CI/CD, SQL, APIs, and OAuth 2.0/OpenID Connect (OIDC).
• Own features across the frontend, backend, data layer, testing, and deployment.
• Demonstrate technical judgment by explaining implemented solutions, architectural decisions, and testing and validation approaches.
Required Qualifications
• Strong software engineering experience with full-stack development across APIs, frontend applications, databases, testing, and troubleshooting.
• Proficiency in Python.
• Experience with React, TypeScript, or another modern frontend framework.
• Hands-on experience with Claude Code, Codex, or similar agentic coding tools.
• Practical experience with LLMs, prompting, structured outputs, tool calling, and RAG.
• Strong understanding of AI evaluation and observability, including runtime validation, telemetry, troubleshooting, and AI quality measurement.
• Experience with Azure and/or GCP.
• Experience with Docker, CI/CD, SQL, APIs, and OAuth 2.0/OIDC.
• Ability to independently own features across frontend, backend, data, testing, and deployment.
• Ability to clearly explain solutions developed, technical decisions made, and methods used to test and validate implementations.
Preferred Qualifications
• Experience with PostgreSQL and pgvector.
• Experience with Kubernetes.
• Experience with ETL and Change Data Capture (CDC).
• Experience with event-driven systems and serverless architectures.
• Experience with Vertex AI or Microsoft Foundry.
• Experience with C# and Go.
