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Ai Risk Jobs in Michigan (NOW HIRING)

AI/RPA Engineer

Kalamazoo, MI · On-site

$175K - $200K/yr

... client risk use cases integrated with Beacon's EHR, eMAR, HRIS, CRM, and incident management ... AI Agent framework supporting: • Task automation • Data retrieval and summarization • ...

Stellantis is a global automotive company seeking an AI Coding Product Leader to define the vision ... risk, and enterprise needs. • Lead the evaluation, rollout, and continuous improvement of ...

Sr Director, AI Transformation

Ann Arbor, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The strategy and priorities are set; this role makes them real in production, at the quality bar a company serving legal, tax, and risk professionals demands. You own AI skills development: the ...

The role owns the management rhythms that keep AI initiatives aligned, transparent, and moving from ... Own risk, issue, action, decision, and dependency tracking, including decision logs, action ...

AI Portfolio / PMO Lead

Novi, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Manage the divisional AI backlog, including demand intake, prioritization support, cohort planning ... Own risk, issue, action, decision, and dependency tracking, including decision logs, action ...

AI Portfolio / PMO Lead

Novi, MI · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Manage the divisional AI backlog, including demand intake, prioritization support, cohort planning ... Own risk, issue, action, decision, and dependency tracking, including decision logs, action ...

Lead Software Engineer, AI

Ann Arbor, MI · Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... tax, risk, and compliance domains. About the Role In this opportunity as a Lead Software Engineer, AI, you will: * Build and architect AI-driven systems - Design and lead the implementation of ...

Showing results 21-40

Ai Risk information

What is the difference between Ai Risk vs Data Scientist?

AspectAi RiskData Scientist
Required CredentialsBackground in AI, risk management, certifications in AI safetyDegree in Computer Science, Statistics, or related fields; certifications in data analysis
Work EnvironmentRisk assessment teams, AI development projects, regulatory settingsData analysis teams, research labs, tech companies
Employer & Industry UsageTech firms, AI safety organizations, regulatory agenciesTech companies, finance, healthcare, research institutions
Common Search & Comparison IntentUnderstanding AI risk roles, career differencesData analysis careers, AI safety roles

Ai Risk professionals focus on identifying and mitigating risks associated with artificial intelligence systems, often working in safety, ethics, and regulatory contexts. Data Scientists analyze large datasets to extract insights, build models, and support decision-making across various industries. While both roles require technical skills, Ai Risk emphasizes safety and ethical considerations, whereas Data Scientists focus on data analysis and modeling.

What are the most commonly searched types of Ai Risk jobs in Michigan?

The most popular types of Ai Risk jobs in Michigan are:

What are popular job titles related to Ai Risk jobs in Michigan?

For Ai Risk jobs in Michigan, the most frequently searched job titles are:

What cities in Michigan are hiring for Ai Risk jobs?

Cities in Michigan with the most Ai Risk job openings:

Infographic showing various Ai Risk job openings in Michigan as of August 2026, with employment types broken down into 73% Full Time, 21% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

$175K - $200K/yr

Full-time

Posted 24 days ago


Beacon Specialized Living rating

5.5

Company rating: 5.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

169th of 242 rated social care providers


Job description

Position Summary:
This role will be responsible for developing secure, compliant AI infrastructure and reusable frameworks that enable internal teams and external consultants to build and deploy AI agents for Operations, Human Resources, Admissions, and IT, while also supporting advanced LLM-driven clinical and client risk use cases integrated with Beacon's EHR, eMAR, HRIS, CRM, and incident management systems.
NOTE: **Applicants must be legally authorized to work in the United States**
Primary Responsibilities:
• Always be compliant with all company and regulatory policies and procedures.
• Design and maintain an enterprise AI Agent framework supporting:
• Task automation
• Data retrieval and summarization
• Workflow orchestration
• Human-in-the-loop approvals
• Build shared services including:
• Prompt management and versioning
• Tool and API integration layers
• Authentication, role-based access, and audit logging
Clinical AI & Client Risk Intelligence
• Develop and support LLM-powered clinical and risk-focused solutions such as:
• Behavioral and incident pattern analysis
• Medication adherence and documentation quality monitoring
• Early-warning indicators for client risk and escalation
• Integrate AI outputs into clinical workflows, dashboards, and alerts.
• Partner with clinical leadership to ensure interpretability and usability of AI insights.
LLM Engineering & MLOps
• Implement and manage LLM integrations including:
• Secure prompt pipelines
• Retrieval-Augmented Generation (RAG) using enterprise data
• Model evaluation and drift monitoring
• Deploy AI services using scalable cloud-native architecture (APIs, containers, CI/CD).
• Optimize performance, cost, and latency across production AI workloads.
Data Integration & Platform Collaboration
• Work with Data Engineering to leverage:
• Microsoft Fabric
• Azure Data Lake
• Power BI semantic models
• Integrate data from:
• EHR and eMAR platforms
Education and Qualifications:
• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 5+ years of experience in software engineering, data engineering, or AI engineering.
• Hands-on experience with:
• LLM APIs and orchestration frameworks
• Prompt engineering and RAG architectures
• API and microservice development

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