Technical Program Manager AI Tools United States Washington Redmond

Job description

Integrated Program Planning: Create and maintain a single, canonical view of Frontier Listening work across full-time and partner teams, including priorities, owners, milestones, dependencies, risks, blockers, and decisions. End-to-End Program Execution: Translate product strategy into actionable plans, sequence work across multiple technical workstreams, drive commitments, and ensure consistent progress toward measurable outcomes. Cross-Functional Alignment: Connect product, engineering, data science, research, marketing, and business stakeholders around shared objectives, priorities, assumptions, and measures of success. Technical Program Leadership: Develop a working understanding of Frontier Listening's knowledge graph, AI experiences, data pipelines, source integrations, and product surfaces in order to challenge plans, identify technical dependencies, and facilitate informed tradeoffs. Operating Model and Rhythm of Business: Establish and continuously improve the planning, standup, review, decision-making, and leadership communication cadences required for the program to operate effectively and predictably. Risk and Dependency Management: Proactively identify ambiguity, delivery risks, cross-team dependencies, and misalignment; bring forward clear options, tradeoffs, and recommendations; and drive issues through resolution. Distributed Team Integration: Plan, track, and review work across full-time employees and offshore engineering partners as one integrated delivery system, with transparent ownership, accountability, and shared context. Decision Enablement: Bring together the right technical, product, customer, and business context so leaders and teams can make timely, informed decisions. Executive Communication: Provide concise, decision-ready updates that clearly communicate what has moved, what is blocked or at risk, what has changed, what happens next, and where leadership input is required. Customer and Business Outcomes: Partner with product and research leads to ensure that program execution remains connected to customer needs, product adoption, decision quality, and business value, rather than treating delivery milestones as the end outcome. Continuous Improvement: Use delivery data, stakeholder feedback, retrospectives, and emerging AI capabilities to improve program health, execution quality, and team effectiveness. Bachelor's Degree in Computer Science, Engineering, Data Science, Information Systems, Business, or a related field AND 2+ years of experience in engineering, product management, technical program management, data science, analytics, or related experience, OR equivalent experience. 1+ years of experience managing cross-functional and/or cross-team projects. Masters Degree in Computer Science, Engineering, Data Science, Information Systems, Business, or a related field AND 6+ years of experience in technical program management, product management, engineering program management, or a related technical discipline. Experience supporting AI, machine learning, generative AI, data science, analytics, knowledge graph, or modern data platform products. Experience working with software engineers, data engineers, data scientists, researchers, and product managers against a shared roadmap. Experience delivering programs involving data ingestion, data quality, model or inference workflows, APIs, agents, knowledge systems, or user-facing product experiences. Experience creating portfolio-level roadmaps or a single integrated view across multiple interconnected technical and business workstreams. Experience managing work across globally distributed teams, vendors, suppliers, or offshore development partners. Experience using Azure DevOps, GitHub, Jira, or similar tools to manage roadmaps, backlogs, dependencies, and delivery health. Experience applying Agile, Lean, or iterative product-development practices while adapting process to the needs of the product and team. Product judgment and customer-centered thinking, including the ability to connect technical delivery to customer problems, product adoption, learning, and business impact. Experience using qualitative research, customer feedback, telemetry, market signals, or other evidence to inform priorities and program decisions. Experience defining success measures and using data to evaluate program health, product outcomes, or operational effectiveness. Experience facilitating executive reviews, product strategy discussions, planning sessions, or cross-organizational decision forums. Ability to translate technical architecture, risks, dependencies, and tradeoffs into plain language for leadership and nontechnical audiences. Demonstrated ability to create clarity and momentum in ambiguous environments through high ownership, thoughtful urgency, and a bias toward action. Ability to build trust quickly, navigate competing priorities, and maintain constructive accountability across organizational boundaries. Experience translating strategies or business objectives into actionable program plans, milestones, ownership, dependencies, and measurable outcomes. Experience independently managing multiple concurrent workstreams and driving execution in an ambiguous or rapidly evolving environment. Experience identifying and mitigating program risks, resolving blockers, and managing cross-team dependencies. Experience establishing or improving program operating mechanisms such as roadmaps, backlogs, delivery reviews, decision logs, status reporting, or rhythms of business. Demonstrated ability to influence, align, and drive accountability across teams without relying on direct authority. Ability to develop a working understanding of complex technical systems and communicate effectively with engineers, data scientists, product leaders, researchers, and nontechnical stakeholders. Written and verbal communication skills, including experience synthesizing complex information into clear recommendations and executive-ready updates. Demonstrated ownership, initiative, and follow-through, including proactively recognizing gaps, creating structure, and closing loops without extensive direction.