Senior AI Architect: GenAI & Agentic Solutions (Remote)

Shrive Technologies LLC; United States; Remote; USD 180,000 - 220,000; Full time

Job summary

Shrive Technologies LLC is seeking an experienced Role AI Architect to design and lead agentic AI solutions in a fully remote U.S. setting.

You will architect end-to-end AI systems, including RAG pipelines, vector DBs, and secure data/AI architectures, collaborating with client IT and business leaders to deliver measurable value. Responsibilities include driving PoCs/MVPs, governing full ML lifecycles, and ensuring compliance with GDPR/CCPA.

Qualifications

• 15+ years of experience in data/AI/ML engineering and architecture.
• Deep hands-on with Azure stack and GenAI tooling.
• Proven ability to design end-to-end AI/ML systems and governance.
• Strong communication with clients and leadership teams.

Responsibilities

• Architect agentic AI solutions using Microsoft Foundry, Azure OpenAI, LangChain, LangGraph, and multi-agent frameworks.
• Lead ML project lifecycles: data prep, modeling, training, evaluation, deployment, and MLOps.
• Govern SDLC for Data, ML, and GenAI platforms with security and compliance controls.
• Design secure, scalable data/AI architectures delivering measurable business value.
• Engage with client IT and business leaders to align on pain points and success metrics.
• Deliver production-ready GenAI/Agentic applications and reproducible experiments.

Skills

15+ years in Data/AI/ML Engineering

Azure stack (Synapse, Fabric, Foundry)

Hands-on ML (forecasting, NLP, DL)

LLMs, embeddings, vector databases, Ra

GenAI tooling (OpenAI APIs, MCP Server

MLOps/LLMOps, CI/CD

XAI, explainability

Security & governance (GDPR, CCPA)

Tools

Microsoft Foundry

Azure OpenAI

LangChain

LangGraph

Autogen

Semantic Kernel

Copilot Studio

Vector DBs

Job description

Shrive Technologies LLC is seeking an experienced Role AI Architect to design and lead agentic AI solutions in a fully remote U.S. setting.

You will architect end-to-end AI systems, including RAG pipelines, vector DBs, and secure data/AI architectures, collaborating with client IT and business leaders to deliver measurable value. Responsibilities include driving PoCs/MVPs, governing full ML lifecycles, and ensuring compliance with GDPR/CCPA.