Senior Gen AI Engineer

Experience: 5 – 6 Years

Job Skills:

Key Responsibilities

• Design and develop end‑to‑end AI and GenAI solutions leveraging Azure AI services.
• Build LLM‑driven applications using Retrieval Augmented Generation (RAG), grounding strategies, and evaluation techniques.
• Develop agent‑based systems using LangChain, LangGraph, Azure Foundry Agents, and Microsoft Agent Framework.
• Apply data science fundamentals to feature engineering, data preparation, retrieval relevance, and model evaluation.
• Develop FastAPI‑based backend services to serve AI workloads at scale.
• Integrate AI solutions with enterprise systems using connectors, APIs, and tool orchestration.
• Work with frontier LLMs (e.g., GPT‑5x, Claude, Gemini, etc.) and select the right model based on cost, latency, reasoning, and accuracy trade‑offs.
• Implement CI/CD pipelines using GitHub Actions and Azure DevOps (ADO).
• Ensure production readiness through logging, monitoring, error handling, and performance optimization.
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  Collaborate closely with Tech Leads, architects, and frontend teams to deliver full‑stack AI solutions.
• Contribute reusable components, accelerators, and internal AI frameworks.

Required Skills & Experience:

AI, Data Science & GenAI

• Strong grounding in data science fundamentals (feature engineering, similarity search, ranking, evaluation, preprocessing).
• Hands-on experience building and optimizing RAG pipelines (chunking, embeddings, retrieval, re-ranking).
• Experience with frontier LLMs, prompt engineering, tool calling, memory, and agent orchestration.

Azure AI & Cloud

• Hands-on with Azure OpenAI, Azure AI Search, AI Studio/Foundry, Blob Storage/Data Lake, Functions, and App Service.
• Experience designing and orchestrating Azure Foundry Agents.
• Solid understanding of Azure security, identity, and enterprise-grade deployments.

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Agentic & LLM Frameworks

• Practical experience with LangChain, LangGraph, and Microsoft Agent Framework.
• Familiarity with vector databases and embedding pipelines.

Engineering & Full Stack

• Strong Python proficiency with production-grade practices.
• Experience building APIs using FastAPI and integrating full-stack applications.
• Hands-on integrating AI systems via REST APIs, tools, connectors, and enterprise data sources.

DevOps & Delivery

• Experience with CI/CD using GitHub Actions and Azure DevOps.
• Understanding of environment promotion, secrets management, and release workflows.
• Familiar with Docker and cloud-native deployment patterns (plus).