Technical Architect Agentic AI / Data & ML

• Architect Agentic AI solutions using Azure OpenAI, LangChain, LangGraph, and multi-agent frameworks.
• Build RAG pipelines, vector database integrations, embeddings, GraphRAG, and autonomous workflow orchestration.
• Lead the complete ML lifecycle, including data preparation, modeling, training, evaluation, deployment, and MLOps.
• Govern the full SDLC for Data, ML, and GenAI platforms.
• Implement Explainable AI (XAI) using technologies such as SHAP and LIME, including fairness and transparency models.
• Architect and deploy solutions across Azure, AWS, and Google Cloud Platform.
• Drive RFP/RFI responses, technical proposals, estimations, solutioning, and client workshops.
• Ensure solutions meet security, compliance, privacy, and governance requirements, including GDPR, CCPA, and PII protection.
• Create architecture blueprints, ML design documents, technical roadmaps, and runbooks.
• Engage with business and IT stakeholders to understand business challenges, priorities, success metrics, and technical risks.
• Design secure, scalable Data and AI solutions that deliver measurable business value.
• Lead architecture and design sessions and develop Data/AI and analytics roadmaps for PoCs and MVPs.
• Support enterprise AI adoption and ensure long-term technical scalability and viability.
• Stay current with emerging AI/GenAI capabilities, technologies, and market trends.
• Mentor technical teams and contribute to technical communities and best practices.

We are seeking an experienced Technical Architect with 15+ years of experience in Data, AI, ML Engineering, and enterprise architecture. The ideal candidate will have strong expertise in the Azure Data & AI ecosystem, along with hands-on experience designing Agentic AI, GenAI, ML, RAG, and multi-cloud solutions., * 15+ years of experience in Data/AI/ML Engineering, Architecture, or related technology domains.

• Strong expertise in the Azure Data & AI stack with working knowledge of AWS and Google Cloud Platform.
• Hands-on experience with Python, PySpark, Azure ML, Databricks, and Scikit-learn.
• Strong experience with LangChain, LangGraph, Agentic AI, LLMs, embeddings, RAG, and GraphRAG.
• Experience with vector databases and AI/ML workflow orchestration.
• Strong understanding of MLOps, LLMOps, CI/CD, SDLC, and enterprise AI deployment.
• Experience with ML techniques including supervised/unsupervised learning, forecasting, NLP, and deep learning.
• Experience implementing Explainable AI (XAI) using SHAP, LIME, fairness, and transparency techniques.
• Strong exposure to Azure Synapse, Microsoft Fabric, Azure Data Factory, Databricks, and Power BI.
• Experience designing secure and scalable enterprise Data/AI platforms.
• Proven experience with RFP/RFI responses, client solutioning, technical proposals, and architecture workshops.
• Strong communication, stakeholder management, architecture, and mentoring skills