Technical Product Manager

About the Role

ActAI aims to transform everyday applications such as email, notes, and calendars by embedding intelligent AI capabilities that require little to no user prompting. Our product focuses on delivering dependable, long-term workflow reliability, maintaining persistent context, and enabling real-world task completion to minimize hallucinations and boost productivity. Our vision is to help users organize their lives effectively so they can focus on meaningful and valuable activities.

Responsibilities

As a Technical Product Manager, you will operate at the crossroads of user demands, AI model functionality, and engineering limitations. Collaborating closely with machine learning and engineering teams, you will define desired system behavior, establish clear metrics for success, and continuously refine the product. This role demands deep technical understanding and a hands-on approach toward systems and decision-making.

• Define comprehensive requirements for AI-related features spanning model performance, system operations, and user experience.
• Interpret machine learning capabilities, evaluation data, and technical constraints into actionable product strategies and system designs.
• Balance trade-offs among factors including quality, response time, cost-efficiency, reliability, safety, and user interface.
• Partner closely with ML, backend, and client engineering teams on system architecture, assessments, and iterative improvements.
• Develop and update evaluation frameworks using offline analyses, live experiments, and human input.
• Set definitive quality benchmarks and design feedback loops for AI-driven experiences.
• Steer project execution via clear specifications, prioritized goals, and informed technical choices.
• Detect potential failure scenarios and guarantee AI systems behave reliably and recover smoothly.
• Ensure high standards across product quality dimensions, including accuracy, dependability, usefulness, and user trust.

Requirements

Technical Expertise

• Robust computer science foundation and proficiency in system design.
• Thorough understanding of contemporary machine learning principles and real-world AI system behaviors.
• Comfortable analyzing technical documentation, system architectures and engaging deeply with engineering teams.
• Insightful grasp of model limitations, hallucination issues, evaluation methodologies, and failure modes.

Product & AI Experience

• Proven track record overseeing complex and technical products from inception to delivery.
• Practical experience with AI-driven products, especially those involving large language models (LLM).
• Familiarity with model evaluation processes, experimentation, prompting strategies, and iterative AI system enhancement.
• Skillful at converting ambiguous problems into precise requirements, measurable targets, and actionable plans.
• Strong decision-making ability, especially in situations with uncertain or incomplete information.

Mindset and Approach

• Highly technical, inquisitive, and unafraid to dive deep into challenges.
• Bias towards rapid deployment, constant experimentation, and deriving insights from real-world usage.
• Capable of constructively challenging technical teams while sustaining collaborative relationships.
• Comfortable assuming significant ownership in dynamic, early-stage environments.

Preferred Qualifications

• Experience launching AI-intensive consumer-facing products.
• Background as an engineer or a technically-oriented product manager.
• Expertise in crafting evaluation metrics specific to machine learning systems.
• Strong understanding of AI user experience design and failure mitigation techniques.
• Prior involvement in zero-to-one product development scenarios.

Outcomes

• Align AI functionality tightly with user needs and corporate objectives through clear product strategy.
• Deliver AI features that provide tangible value, are reliable, easy to understand, and earn user trust.
• Make well-balanced decisions factoring in quality, speed, cost, and reliability despite uncertainty.
• Maintain transparent roadmaps and priorities that evolve quickly based on real user feedback.
• Facilitate well-coordinated teams able to achieve AI product milestones efficiently and with minimal obstacles.

Work Culture

Our small, highly skilled team emphasizes broad ownership and independent, sound judgment. We prioritize quick decision-making, close cooperation, and balancing rapid progress with engineering fundamentals. Process is secondary to outstanding results.

Interview Process

Candidates fitting the requirements will undergo three to four interview rounds, conducted virtually or onsite, with evaluations led by technical team members. Prompt decisions and offers are expected for those demonstrating exceptional capabilities and mindset. Joining us means becoming part of a mission to bring practical AI benefits to billions worldwide.