Job Description :

- 6 to 8+ years of experience in software, AI, or ML engineering roles, including significant experience designing, delivering, and operating production-grade GenAI or agentic AI applications.

- Proven experience leading the technical delivery of LLM-powered products or agent-based solutions, including solution design, engineering guidance, and operational readiness.

- Strong technical foundation in Python and modern backend engineering patterns, with practical experience building AI-enabled application services and APIs.

- Hands-on experience with Azure OpenAI, Azure AI Studio, Semantic Kernel, LangChain, AutoGen, or equivalent platforms and orchestration frameworks, including real-world use of LLM APIs, prompt workflows, tool calling, and agent coordination.

- Strong experience designing and implementing retrieval-augmented generation (RAG) and vector-based patterns using platforms such as Azure AI Search, Pinecone, Weaviate, FAISS, or equivalent.

- Experience building and deploying cloud-native AI services using technologies such as Azure Functions, Azure Container Apps, FastAPI, Docker, Azure DevOps, GitHub, or equivalent engineering and deployment platforms.

- Solid understanding of CI/CD, containerization, automated testing, and production deployment practices for AI-driven systems.

- Practical experience with observability and operational tooling such as Application Insights, OpenTelemetry, Azure Monitor, Datadog, New Relic, or equivalent, including monitoring of reliability, latency, and cost.

- Exposure to Model Context Protocol (MCP), agent-to-agent (A2A) interaction patterns, or similar context-sharing and distributed agent communication approaches.

- Strong ownership mindset across the full SDLC, including design, build, deployment, support, reliability improvement, and long-term maintainability.

- Proven ability to raise engineering quality through code reviews, technical mentoring, design guidance, and reuse of shared patterns and components.

- Strong collaboration and communication skills, with the ability to work effectively across engineering, architecture, product, and platform teams.