AI Architect

Job Description

Job Description

Key Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks
• Build AI solutions using frameworks such as Microsoft Agent Framework – Autogen, Semantic Kernel, Copilot Studio
• Well-versed with the Microsoft Agentic Framework (MAF)
• Build RAG pipelines, vector DB integrations & autonomous workflow orchestration
• Design and lead ML project lifecycles — data prep, modeling, training, evaluation, deployment & MLOps
• Govern full SDLC for Data, ML, and GenAI platforms
• Ensure strong security, compliance, governance (GDPR, CCPA, PII)
• Produce robust architecture blueprints, ML design docs, and runbooks
• Engage with customer IT and business leaders to understand pain points, priorities, success measures, and risks.
• Design secure, scalable data and AI solutions to deliver measurable business value.
• Lead architecture design sessions, develop data/AI and analytics roadmaps to drive PoCs and MVPs.
• Accelerate adoption and ensure long-term technical viability.
• Deliver Production-ready GenAI/Agentic applications.
• Fine-tuned models and reproducible experiments.
• Provide Clear documentation, test coverage, and deployment pipelines.
• Regular updates on project status and deliverables to stakeholders.
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops

• 15 years in Data/AI/ML Engineering
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Azure App Insights
• Hands-on with:

• • ML projects (supervised/unsupervised, forecasting, NLP, deep learning)
  • ML modeling tools: Python, PySpark, Azure ML, Databricks, Scikit-learn
  • Microsoft Foundry, Microsoft Agentic Framework
  • LLMs, embeddings, vector databases, RAG/GraphRAG, prompt optimization, and safety/guardrails
  • GenAI tools: MCP Server, Hugging Face Transformers, OpenAI APIs, and diffusion models (for image generation).
  • CI/CD, MLOps/LLMOps, SDLC
  • Explainable AI (XAI)

• Cloud certifications (Microsoft Azure) is a plus