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Ai Implementation Jobs in Rochester Hills, MI (NOW HIRING)

Megan soft Inc

Senior AI/ML Engineer

Dearborn Heights, MI · On-site

$96K - $132K/yr

Demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs. * Strong technical expertise ...

OpTech

AI Specialist

Pontiac, MI · On-site

... AI implementation across multiple business units. This role combines strategic oversight with hands-on program management to maximize the value of AI technologies while maintaining compliance ...

New

KYYBA Inc

Cyber Security Architecture Manager

Detroit, MI · On-site

$109K - $148K/yr

... implementation of applications and platforms. • Support AI-related security initiatives, including governance, risk management, and secure AI adoption strategies. • Drive cloud security ...

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All JobsAi Implementation JobsAi Implementation Jobs in Rochester Hills, MI

Ai Implementation information

See Rochester Hills, MI salary details

$35.9K

$95.3K

$154.6K

How much do ai implementation jobs pay per year?

As of Aug 21, 2026, the average yearly pay for ai implementation in Rochester Hills, MI is $95,284.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,500.00 and $111,400.00 per year, depending on experience, location, and employer.

What is an AI implementation?

An AI Implementation job involves deploying artificial intelligence solutions within an organization to improve efficiency, automation, and decision-making. Professionals in this role work closely with data scientists, engineers, and business teams to integrate AI models into existing systems. They manage data pipelines, ensure model performance, and address challenges related to scalability and compliance. Strong technical skills, project management, and an understanding of business processes are essential for success in this role.

What are the key skills and qualifications needed to thrive in the AI implementation position?

To excel in AI Implementation, you need a robust understanding of machine learning concepts, data analysis, and software development, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, cloud platforms (AWS, Azure), and AI integration frameworks is commonly required, along with relevant certifications. Strong project management, problem-solving abilities, and excellent communication skills are crucial for coordinating with stakeholders and driving adoption. Mastering both technical and interpersonal skills ensures projects are delivered effectively and meet business objectives within diverse organizational settings.

What kinds of teams and departments does an AI implementation professional typically collaborate with?

AI Implementation professionals usually work cross-functionally, interacting with data scientists, software engineers, IT departments, and business stakeholders to ensure AI solutions address specific business needs. Regular collaboration with product managers and operations teams helps align technical efforts with strategic objectives and regulatory requirements. You may also work closely with end users to gather feedback, refine implementations, and ensure a smooth adoption process. This collaborative environment not only enhances the quality of AI deployments but also offers valuable exposure to different aspects of the organization, fostering professional growth.

How to become an AI implementation specialist?

To become an AI implementation specialist, individuals typically need a strong background in computer science, data science, or related fields, along with knowledge of machine learning, programming languages like Python, and AI frameworks such as TensorFlow or PyTorch. Gaining experience through internships, certifications, or projects involving AI deployment is also valuable. Continuous learning and staying updated on AI tools and industry trends are essential for success in this role.

How to get into AI implementation?

To pursue a career in AI implementation, develop strong skills in programming languages such as Python, understand machine learning frameworks like TensorFlow or PyTorch, and gain experience with data analysis and model deployment. Earning relevant certifications or degrees in computer science, data science, or AI can also enhance your qualifications.

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Ai Implementation jobs near you
Infographic showing various Ai Implementation job openings in Rochester Hills, MI as of August 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $95,284 per year, or $45.8 per hour.

Senior AI Implementation Technical Lead

Proactive Technology Management

Detroit, MI • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 days ago

Job description

What This Role Is
This is a hands-on engineering role with client-facing responsibility.
You should enjoy writing code, solving technical problems, and working through ambiguity. Some projects will be clean and well-defined. Others will involve messy data, unclear system boundaries, changing requirements, or legacy client environments.
The right person can stay practical, communicate clearly, and keep moving toward a working solution.
You do not need to know every tool in our stack on day one. You do need to be a strong engineer who can learn quickly and take ownership.
What You Will Do
You will help take approved client projects from idea to working production software.
Your work may include:
  • Building web applications, APIs, backend services, and AI-enabled workflows
  • Integrating with client databases, file systems, business applications, and APIs
  • Building AI tools that help automate manual work
  • Creating secure, reliable deployments in Azure
  • Setting up logging, monitoring, authentication, and environment configuration
  • Working with another engineer to plan and build features
  • Joining technical client meetings, demos, and architecture discussions
  • Helping estimate work and break projects into clear milestones
  • Documenting what was built so the client and PTM team can support it after launch

You will not be responsible for running the full discovery process or leading executive workshops. Our Discovery team handles that upstream. Your role begins when the client is ready to build.
Example Projects You Might Work On
You may help build solutions such as:
  • An AI assistant that helps staff search internal documents or policies
  • A document intake process that extracts information from PDFs, emails, or forms
  • A workflow automation tool that reduces manual approvals or handoffs
  • A dashboard or internal portal connected to client systems
  • An AI-powered review process with human approval before final action
  • A data pipeline that moves, cleans, or prepares information for reporting or automation
  • A custom application that connects multiple systems into one usable workflow

The goal is always the same: build practical technology that saves time, reduces errors, improves visibility, or creates measurable business value.
The Stack We Commonly Use
PTM is Azure-first, but we care more about strong engineering ability than exact tool matching.
Our common stack includes:
  • Backend: Python, FastAPI, Pydantic, ASP.NET Core, C#
  • Frontend: React, TypeScript, Vite, Azure Static Web Apps
  • Cloud: Azure Container Apps, Azure Functions, Azure SQL, Key Vault, Azure Storage
  • AI: Azure AI Foundry, OpenAI, Anthropic, agent-based workflows, structured AI outputs
  • Infrastructure: Bicep, Azure Developer CLI, GitHub Actions, Docker
  • Data: Azure SQL, Dataverse, Microsoft Fabric, Azure AI Search, PostgreSQL
  • Monitoring: Azure Monitor, Application Insights, Log Analytics, structured logging
  • Identity: Microsoft Entra ID, Auth0, Okta, Google Workspace, generic OIDC

You do not need deep experience in every item above. Strong experience in backend development, cloud applications, APIs, databases, and modern software delivery is more important.
What We Are Looking For
We are looking for a smart, hard-working engineer who can build reliable software and work well in client environments.
You are probably a strong fit if you can:
  • Build and deploy production software
  • Work across backend, frontend, cloud, and data as needed
  • Learn new tools quickly
  • Read a project plan and turn it into an engineering plan
  • Break large problems into smaller deliverables
  • Write clean, maintainable code
  • Communicate technical decisions clearly
  • Work with another engineer without needing constant direction
  • Handle client technical conversations professionally
  • Stay calm when requirements are imperfect or systems are messy

This role requires ownership. We are looking for someone who does not wait to be told every next step.
Requirements
We are looking for most of the following:
  • 4+ years of professional software engineering experience
  • Strong backend development experience in Python, C#, or a similar language
  • Experience building APIs, services, or full-stack applications
  • Experience with relational databases such as SQL Server, Azure SQL, PostgreSQL, or similar
  • Experience deploying applications to a cloud platform
  • Comfort using Git, pull requests, CI/CD, and modern development workflows
  • Ability to troubleshoot production issues
  • Ability to work directly with technical and non-technical stakeholders
  • Strong written and verbal communication skills
  • US work authorization

Azure experience is strongly preferred, but equivalent AWS or GCP experience is acceptable if you are willing to learn Azure quickly.
Nice to Have
These are helpful, but not required:
  • Azure Container Apps, Azure Functions, Azure Static Web Apps, or Key Vault
  • FastAPI, Pydantic, or ASP.NET Core
  • React and TypeScript
  • AI application development or LLM-based tools
  • OpenAI, Azure AI Foundry, Anthropic, or similar platforms
  • Document processing, OCR, or data extraction
  • Workflow automation, RPA, or low-code tools
  • Infrastructure as Code experience with Bicep, Terraform, or similar
  • Observability experience with Application Insights, Azure Monitor, OpenTelemetry, or structured logging
  • Healthcare, insurance, finance, manufacturing, logistics, or other complex industry experience
  • HIPAA, compliance, privacy, or regulated data experience

Healthcare experience is a bonus, not a requirement.
What Success Looks Like
In your first year, success means you are able to:
  • Lead the technical build on several client implementation projects
  • Turn approved project roadmaps into working software
  • Ship useful features against agreed milestones
  • Deploy solutions into client Azure environments
  • Communicate clearly with clients and internal teams
  • Identify risks early and raise them before they become major issues
  • Create clean documentation and handoff materials
  • Help improve PTM's reusable implementation patterns

You will not be alone. Most projects include another engineer, support from the Discovery team, and review from technical leadership. But you are expected to own your work and drive toward delivery.
Benefits
Possibility of contract-to-hire
  • Full Medical Benefits
  • 2 Weeks Paid Vacation
  • Full Time
  • Dental & vision insurance
  • 401(k) matching

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