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.
- 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.
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).
