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Agentic Ai Engineer Jobs in Michigan (NOW HIRING)

Sr. AI Engineer

Southfield, MI · On-site

$95K - $131K/yr

Our APEX team owns the AI and engineering platform that the rest of the company builds on, and we ... You will own the implementation of our agentic platform - the harness, the agent pipelines, the ...

Agentic frameworks (LangChain, LlamaIndex, or AWS Bedrock Agents) Development Stack: * Python (AI ... Prompt engineering & optimization * Model evaluation & testing frameworks * AI observability ...

AI Engineering Skills (Two or More) * Agentic AI: building and integrating autonomous AI agents using LLM APIs and orchestration frameworks (e.g., Anthropic Claude, OpenAI GPT, LangChain, CrewAI ...

As a Senior AI Engineer - Cybersecurity , you will design, build, and deploy AI-powered solutions ... Build and improve agentic workflows that automate repetitive, high-volume security tasks and ...

Data Engineer - Supply Chain

Auburn Hills, MI · On-site

$108K - $130K/yr

... and agentic AI solutions across the Supply Chain organization. This role focuses on production ... The Data Engineer partners closely with Data Science, AI Engineering, Automation, and Platform ...

Senior Engineer, AI

Novi, MI · On-site

$90.75 - $133.10/hr

Engineer audio systems and integrated technology platforms that augment the driving experience ... The primary focus remains on generative AI, LLMs, agentic workflows, retrieval‑augmented ...

Showing results 41-60

Agentic Ai Engineer information

See Michigan salary details

$34K

$88.7K

$119.8K

How much do agentic ai engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for agentic ai engineer in Michigan is $88,687.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,200.00 and $101,500.00 per year, depending on experience, location, and employer.

What does an agentic AI engineer do?

An agentic AI engineer designs and develops autonomous AI systems capable of making decisions and taking actions independently. They work with machine learning models, reinforcement learning, and AI frameworks to create systems that can adapt and operate in dynamic environments, often requiring knowledge of programming, data analysis, and AI ethics.
What are popular job titles related to Agentic Ai Engineer jobs in Michigan? For Agentic Ai Engineer jobs in Michigan, the most frequently searched job titles are:
What cities in Michigan are hiring for Agentic Ai Engineer jobs? Cities in Michigan with the most Agentic Ai Engineer job openings:
Infographic showing various Agentic Ai Engineer job openings in Michigan as of August 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 60% In-person, and 40% Remote job distribution, with an average salary of $88,687 per year, or $42.6 per hour.

Sr. AI Engineer

Barton Malow

Southfield, MI • On-site

$95K - $131K/yr

Full-time

Posted 26 days ago


Barton Malow rating

7.4

Company rating: 7.4 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

About Barton Malow

Barton Malow is a builder. For over 100 years we have delivered some of the most complex construction projects in North America - schools, hospitals, stadiums, manufacturing plants, and industrial facilities. Today we are doing something most construction companies are not: rebuilding how we build software, with AI at the center. Our APEX team owns the AI and engineering platform that the rest of the company builds on, and we are investing seriously in it.

About the role

We are hiring a Senior AI Engineer to build the systems that make AI agents do real, reliable work across Barton Malow. This is a deep, hands-on, senior individual-contributor role. You will own the implementation of our agentic platform - the harness, the agent pipelines, the evaluation infrastructure, and the production systems that turn AI from a prototype into something teams depend on every day.

By "harness" we mean the machinery that makes autonomous AI reliable: the orchestration loop, the tool and data integrations, the testing and evaluation gates, the observability layer, and the deployment infrastructure around the models. Building that machinery - and keeping it running in production against real data and real workflows - is the job.

This is not a role at a software company, and it is not a role where you write a little code on the side. It is a role building the foundation an entire organization will run AI on for the next decade. The portfolio is messy, the problems are real, and the mandate is clear.

What you'll do

Build the harness. Implement the core machinery that makes AI agents reliable: the orchestration loop, the tool-execution and integration layer, evaluation gates, state persistence, error recovery, and the observability that makes agent behavior legible. The models change; the harness you build is what lasts.

Ship agentic systems to production - and keep them reliable. Take AI systems from prototype to production: deployment, monitoring, rollback, controlled release, and the self-healing loops that detect and recover from failures. The bar is not a demo - it is autonomous systems running against real Barton Malow data and workflows, reliably, with you accountable for correctness and uptime.

Build the evaluation and verification infrastructure. Verification is what separates a demo from production. You will build the evaluation harness, the regression suites, the deterministic gates (tests, linters, contract checks), and the automated judging infrastructure that lets us prove AI output is correct before it ships.

Build the platform substrate. Implement the production components that connect AI agents to Barton Malow's real systems and data - Autodesk, SAP, Databricks, and a growing set of external services - and the interfaces people use to work with those agents.

Set the engineering bar by example. As one of the most senior engineers on the team, you set the implementation patterns, write the reference code others build on, review at depth, and raise the quality of everyone working alongside you.

What we're looking for
  • 10+ years in software engineering, with demonstrated depth as a senior individual contributor who ships complex systems to production
  • Hands-on experience building and operating production AI or agentic systems - not just using AI tools in your own workflow. You have taken an LLM- or agent-powered system to production and kept it running
  • Experience implementing the components behind reliable AI systems: orchestration, tool/function calling, evaluation, context management, and handoffs between steps or agents
  • Strong software engineering fundamentals - testing, CI/CD, observability, error handling - applied to the realities of nondeterministic AI systems
  • Production cloud operations, ideally AWS: architecting, deploying, and operating real workloads
  • Data and integration experience: building pipelines that move data reliably between enterprise systems (ERP, SaaS APIs, data warehouses or lakehouses)
  • A pragmatic builder's instinct: you build the reusable thing, iterate in production, and know when shipping behind a flag beats perfecting on paper
  • Strong communicator who can work with engineers, managers, and executives and adjust the level for each
Nice to have
  • Hands-on experience with an agent framework or SDK and with multi-agent or planner/generator/evaluator architectures
  • Experience building evaluation frameworks or automated AI-judging systems
  • Experience with Databricks or a similar lakehouse platform
  • Experience building tool-integration layers (e.g., MCP servers) between AI systems and enterprise applications
  • Experience in a non-software-company engineering organization - internal tools, corporate IT transformation, or similar
  • Open-source contributions or public work that shows how you build
Why this role

You will build the platform an entire organization runs AI on, with a clear mandate and a direct line to the Director of APEX. The platform is early - that is the appeal. You are not maintaining someone else's infrastructure; you are building the harness Barton Malow will use for the next decade. When the models get better, the infrastructure you build is what lets the company capture it.

Barton Malow is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability status, genetic information, protected veteran status, or any other legally protected characteristic.


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