AI Architect

Shrive Technologies LLC; Town of Texas (WI); On-site; USD 170,000 - 230,000; Full time

Job summary

Shrive Technologies LLC seeks an experienced Data/AI/ML Engineer to architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, and multi‑agent frameworks.

You will design and lead ML lifecycles, build RAG pipelines and secure data/AI platforms, while collaborating with client IT leaders to deliver production‑ready GenAI applications. 15+ years required, strong Azure expertise.

Qualifications

• 15+ years in Data/AI/ML Engineering.
• Expertise in Azure stack including Synapse, Fabric, Foundry, Copilot Studio.
• Hands-on ML projects with Python, PySpark, Azure ML, Databricks, Scikit-learn.
• Experience with LLMs, embeddings, vector databases, RAG/GraphRAG, prompt optimization, safety.

Responsibilities

• Architect Agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph & multi-agent frameworks.
• 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.
• Engage with customer IT and business leaders to understand pain points, priorities, success measures, and risks.
• Deliver Production-ready GenAI/Agentic applications.

Skills

Data/AI/ML Engineering

Azure AI / Foundry

ML/Ops & SDLC

NLP / Deep Learning

Python / PySpark

LLMs / Embeddings

RAG / GraphRAG

Tools

Microsoft Foundry

Microsoft Agentic Framework

Azure Synapse

Databricks

Hugging Face Transformers

Job description

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