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Tech AI Program Manager

Tanisha Systems

  • Chicago, IL, IL
  • 7 days ago
  • $180,000–$200,000 Per Year
  • Full-time
  • Employee

Highlights

Full-Lifecycle Technical Product Ownership: Demonstrate success taking a platform product from initial user research and technical design to deployment, internal enablement, and high adoption across multiple engineering teams. Measure and Optimize Impact: Define, track, and optimize technical success metrics (e.g., agent reliability, processing latency, accuracy thresholds) to ensure the platform genuinely accelerates engineering velocity.

Numbers & Facts

LocationChicago, IL, IL
Job TypeFull-time, Employee
Salary$180,000–$200,000 Per Year

Description

Job Title: Tech AI Program Manager
Location: Chicago, IL 1 st Preference
Remote Option: If a candidate has a strong background and relevant experience, we can check with the client regarding a remote work option.

Salary - Market

We are seeking a hands-on, deeply technical Program Manager (TPM) to drive the execution of our next-generation AI Developer Experience (DX) platform.
  • Own the AI Skill & Agent Lifecycle: Research, design, and deliver high-impact AI skills and autonomous agents that solve real-world problems for various internal engineering teams.
  • Drive Platform Adoption: Partner closely with developer teams to ease onboarding, capture feedback, and ensure deep user adoption of newly shipped AI platform capabilities.
  • Bridge Engineering and Product Management: Act as a strategic translator by understanding internal developer pain point s, researching industry solutions, and defining technical requirements that match user needs.
  • Measure and Optimize Impact: Define, track, and optimize technical success metrics (e.g., agent reliability, processing latency, accuracy thresholds) to ensure the platform genuinely accelerates engineering velocity.
  • Full-Lifecycle Technical Product Ownership: Demonstrate success taking a platform product from initial user research and technical design to deployment, internal enablement, and high adoption across multiple engineering teams.

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