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Technical Project Manager Digital Engineering, AI & Data :: Northville, MI

Reliable Software ResourcesNorthville, MI🇺🇸United StatesPosted Sep 21, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Northville, MI, United States
Posted
1 week ago
SAFeNode.jsAWSMachine LearningSnowflakeAgileAngularAzureDatabricks.NETGoogle CloudJavaJiraPythonReact

Job Description

Technical Project Manager – Digital Engineering, AI & Data
Location: Northville
Type: Full-time
About the Role
Our engineers, AI developers, and data specialists are what we deliver, and we want every engagement to land. As Technical Project Manager, you'll keep our onshore and offshore teams on track and make sure the applications, AI solutions, and data platforms we build match what the client actually asked for. You'll partner closely with our Delivery Manager: they own the client relationship, and you make sure we deliver on it. You have the technical depth to review modern engineering and AI work, and the leadership to get the best out of a distributed team across the US and India.
What You'll Do
  • Plan and run projects end to end across full-stack application development, GenAI solutions, and data engineering, including scope, milestones, sprints, status reporting, and sign-off.
  • Hold regular check-ins with engineers and consultants on progress, blockers, workload, and morale.
  • Translate client requirements into clear technical deliverables and acceptance criteria, and confirm the team's work matches them.
  • Manage GenAI projects with the right approach: define success metrics up front, set realistic expectations on accuracy and iteration, and guide the path from proof of concept to production.
  • Set up quality practices such as code reviews, automated testing, CI/CD, data validation, and AI output evaluation.
  • Make sure solutions account for security, responsible AI, and data privacy requirements.
  • Turn delivery issues raised by the Delivery Manager into action plans and drive them to resolution.
  • Coordinate onshore and India-based teams across time zones so handoffs are clean and deadlines hold.
  • Identify skill gaps and arrange training or mentoring, especially on fast-moving AI tools and frameworks.
  • Watch for retention risks and work with HR and Recruiting on backfills.
  • Build repeatable templates and playbooks for common engagement types, such as app builds, GenAI pilots, modernization, and data platform projects.
What You Bring
  • 8+ years in IT, with at least 4 years managing software development projects.
  • A hands-on engineering background with enough depth to review architecture and code and earn engineers' respect.
  • Experience delivering full-stack applications using technologies such as [React/Angular, Node.js, Java, Python, .NET] on [Azure/AWS/Google Cloud Platform].
  • Experience managing GenAI or AI/ML projects using tools such as [OpenAI, Anthropic Claude, Azure OpenAI, AWS Bedrock, LangChain, vector databases].
  • Familiarity with data platforms such as [Snowflake, Databricks] and modern DevOps practices.
  • A track record of managing distributed onshore/offshore teams.
  • Strong Agile skills and tools such as Jira or Azure DevOps.
  • Clear, calm communication under pressure.
  • Bachelor's degree in Computer Science, Engineering, or a related field.
Nice to Have
  • PMP, CSM, or SAFe certification.
  • Cloud or AI certifications, such as Azure AI Engineer or AWS Machine Learning.
  • Experience with AI evaluation, LLMOps, or data annotation and labeling workflows.
  • Background in IT consulting or services.
What a Rockstar Looks Like
  • Engineers see you as their advocate and the person who clears the path.
  • What the team ships matches what the client asked for the first time.
  • Your GenAI pilots have clear success criteria and a real path to production.
  • Every project you run leaves behind a playbook that makes the next one faster.
How Success Is Measured
  • On-time, on-budget milestone delivery
  • Deliverable acceptance rate and rework levels
  • GenAI pilots advanced to production
  • Consultant retention and satisfaction
  • Number and severity of client escalations

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