Senior Technical Architect

Job Summary

Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks
• 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
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops
• 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.

Skill & Experience

• 15+ years in Data/AI/ML Engineering or 15+ years
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Databricks, Power BI
• 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
• CI/CD, MLOps/LLMOps, SDLC
• Explainable AI (XAI)

Key Responsibilities

Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks
• 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
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops
• 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.

Skill & Experience

• 15+ years in Data/AI/ML Engineering or 15+ years
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Databricks, Power BI
• 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
• CI/CD, MLOps/LLMOps, SDLC
• Explainable AI (XAI)

Skill Requirements

Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks
• 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
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops
• 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.

Skill & Experience

• 15+ years in Data/AI/ML Engineering or 15+ years
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Databricks, Power BI
• 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
• CI/CD, MLOps/LLMOps, SDLC
• Explainable AI (XAI)

Other Requirements

Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks
• 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
• Drive RFP/RFI solutioning, technical proposals, estimations & client workshops
• 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.

Skill & Experience

• 15+ years in Data/AI/ML Engineering or 15+ years
• Strong exposure to Microsoft Azure stack including Synapse, Fabric, Foundry, Copilot Studio, Databricks, Power BI
• 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
• CI/CD, MLOps/LLMOps, SDLC
• Explainable AI (XAI)