AI Solutions Architect - Governance & Partner Oversight

TEKsystems; United States; Hybrid; USD 110,000 - 123,000; Full time

Benefits offered by this job

Health benefits

401(k) retirement plan

PTO / Leave

Job summary

TEKsystems is seeking an experienced AI Architect to guide partner-led AI initiatives on a Microsoft Azure-based data and AI platform. The role focuses on governance and oversight, serving as the internal SME to ensure chatbots and agentic AI workflows meet our exacting standards and deliverables.

You will review designs, validate architectures, and engage stakeholders, driving quality and cost efficiency in enterprise AI deployments.

Qualifications

• 8+ years of experience, including 2+ years in GenAI/LLM development.
• Hands-on with LLMs, RAG, embeddings, vector search and tool/function calling.
• Experience with unstructured data processing (PDF, OCR, images).
• Strong Python development, API integration, and AI frameworks exposure.

Responsibilities

• Provide AI governance and oversight for partner-delivered solutions.
• Review partner designs, validate architecture for scalability and cost.
• Engage stakeholders and ensure requirements are understood and implemented.
• Monitor lifecycle quality and AI observability across projects.
• Navigate enterprise processes and drive strategic alignment.

Skills

GenAI development

AI agent workflows

Prompt engineering

LangChain / LangGraph

Python development

Data processing (PDF OCR)

Embeddings / vector search

AI evaluation frameworks

Model serving / MLflow

Azure data platform

Tools

LangChain

LangGraph

Databricks AI

AI Functions

AI Search/Vector Search

MLflow

Job description

TEKsystems is seeking an experienced AI Architect to guide partner-led AI initiatives on a Microsoft Azure-based data and AI platform. The role focuses on governance and oversight, serving as the internal SME to ensure chatbots and agentic AI workflows meet our exacting standards and deliverables.

You will review designs, validate architectures, and engage stakeholders, driving quality and cost efficiency in enterprise AI deployments.