Architect and build agentic AI solutions using Microsoft frameworks and multi-agent systems. Lead the full ML project lifecycle, including data preparation, modeling, deployment, and MLOps governance.
Role AI Architect
Job Summary
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
Key Responsibilities
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
Skill Requirements
Skill & Experience
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
This is a remote position.
Automatically Apply to the Best Remote Jobs
Stop the endless job search. Our AI finds and applies to the best jobs for you.
Try it Now
— Sarah J.
·
Marketing Manager
★★★★★
Verified
