About the Role
We are looking for an AI Engineer to design, build, and ship AI-powered features in our product on the Microsoft Azure stack. You will own the full lifecycle, from prototype to secure, scalable production deployment, with security, privacy, and responsible AI as first-class requirements rather than afterthoughts.
Team: AI Platform / Product Engineering
Key Responsibilities
- Build and deploy LLM and generative AI features (RAG, copilots, agents, document intelligence) using Azure OpenAI Service, Azure AI Foundry, and Azure AI Search.
- Develop and operationalize ML models with Azure Machine Learning, including MLOps pipelines, model registry, and monitoring.
- Integrate Azure AI Services (Document Intelligence, Speech, Language, Vision, Content Safety) into product workflows.
- Implement guardrails against prompt injection, data leakage, jailbreaks, and harmful output using Azure AI Content Safety, input/output filtering, and red-teaming practices.
- Build backend services and APIs in Python and/or C#/.NET, deployed on AKS, Azure Functions, or App Service.
- Set up CI/CD with Azure DevOps or GitHub Actions and Infrastructure as Code (Bicep/Terraform).
- Partner with product, security, and compliance teams on threat modeling, audits, and responsible AI reviews.
Required Skills
- 6 years in software/AI engineering with strong Python (C#/.NET a plus).
- Hands-on experience with Azure OpenAI, Azure AI Search, Azure ML, and Azure AI Services.
- Practical knowledge of LLM patterns: RAG, embeddings, prompt engineering, function calling, and agent frameworks (Semantic Kernel, LangChain, or AutoGen).
- Solid Azure fundamentals: Entra ID (Azure AD), Managed Identity, Key Vault, Private Link, NSGs, Azure Policy.
- Understanding of AI/application security: OWASP Top 10 for LLMs, secure SDLC, data privacy (PII handling, data residency).
- Experience with containers, Docker, REST APIs, and CI/CD.