Manager of Artificial Intelligence

Job Summary

The Technical Product Manager (TPM) is the functional engine of the product team, responsible for the high-fidelity execution of the strategic product vision. In this role, you will partner closely with leadership to deconstruct a high-level vision into clear, developer‑ready requirements. You are the bridge between "what is possible" and "how it is built," ensuring that complex data workflows and AI‑driven logic are executed with precision, speed, and accuracy.

Key Duties and Responsibilities (including but not limited to)

Strategic Execution & Translation

• Vision Translation: Partner with leadership to break down complex strategic visions into simple, granular requirements for the development team.
• Instructional Authoring: Author the "Instruction Manual" for the product, defining exactly how logic and data move through the system from start to finish.
• Tactical Roadmap Maintenance: Manage the release schedule and feature priorities to ensure the product evolves in lockstep with the strategic vision.

Execution & Delivery

• Daily Execution: Manage the daily list of bugs and features, making decisions on immediate fixes versus post‑launch enhancements.
• Sprint Planning: Work with Program Management to define priorities and plan upcoming sprints based on the overarching product goals.

Quality & Alignment

• UAT Facilitation: Provide the documentation and product knowledge needed for the UAT team to test effectively and verify the strategic intent.
• Bug Verification: Filter and verify bugs reported by testers to ensure only legitimate, high‑priority issues are passed to the engineering team.

Stakeholder Coordination

• Point of Contact: Serve as the main point of contact for PMO and Operations, providing updates on technical progress and delivery timelines.
• Feedback Triage: Gather feedback from departments and organize it into a structured triage plan or decision matrix for leadership review.

Success Metrics

• Vision Fidelity: How accurately the final technical build reflects the original strategic vision provided by leadership.
• Requirement Clarity: Minimal "blocked" status for developers due to missing or ambiguous technical specs.
• User Delight & Resonance: High levels of stakeholder satisfaction, evidenced by frictionless product use and enthusiastic advocacy from cross‑functional partners.
• Value & ROI: Measurable success in driving value for customers and increasing ROI through cost savings or revenue gains.
• Delivery Predictability: Maintaining a consistent release cadence that aligns with the established roadmap.

Knowledge and Skills

Systems Integration & Cloud Infrastructure

• Cloud Platform Familiarity: Practical understanding of how cloud platforms store data and run automated tasks to process information.
• Data Flow Logic: Experience mapping out how information moves from one system to another, ensuring data integrity as it transitions from routing services to cloud databases.
• System Connectivity: Understanding how different software tools "talk" to each other to send data payloads and confirm when a task has been completed successfully.

AI‑Driven Logic & Problem Solving

• Execution of AI Vision: Practical experience using Large Language Models (LLMs) to perform complex reasoning and solve multi‑step problems based on a defined strategic framework.
• Algorithmic Deconstruction: Ability to take a high‑level "thinking" task and break it down into a series of logical inferences, evaluations, and summaries that an AI can execute.
• Performance Optimization: Basic understanding of managing "token limits" and the trade‑offs between a model’s "thinking" time and its operational speed/cost.
• Exception Logic: Ability to define "if/then" rules for when AI reasoning is inconclusive, ensuring a robust hand‑off to human‑in‑the‑loop validation.

Product Lifecycle & Tactical Delivery

• Technical Documentation: Expertise in writing step‑by‑step user stories and product descriptions that provide developers with a flawless blueprint for building.
• Backlog Management: Proficiency in enterprise project management tools (e.g., ADO) to track bugs, prioritize new features, and maintain the tactical roadmap.
• Testing Coordination: Ability to translate technical requirements into accurate scripts for testing teams to verify product intent.

Experience

• 3‑5 years in a product management or technical product management role
• AI/LLM Experience: 1+ year of experience (or equivalent project work) architecting multi‑step AI reasoning workflows, including API integration, prompt engineering for logical output, and exception handling.

Education & Certifications

• Bachelor’s degree in a quantitative or technical field (e.g., Computer Science, Engineering, Mathematics, or Information Systems) or equivalent practical experience in a technical product environment
• Certifications (Preferred): Agile/Scrum certifications (CSPO or CSM) or cloud‑specific foundational certifications (GCP Digital Leader or AWS Cloud Practitioner)