Technical Product Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of platform features from the initial intake to scoping, building, demoing, and launching.

• Collaborate with the CTO and Head of AI Product to determine what is ready for development and clearly communicate the plan and reasoning behind it.

• Conduct demonstration sessions and establish a feedback loop, recording insights in Linear.

• Convert validated directions into comprehensive product requirements, explicit scopes, non-goals, success metrics, and acceptance criteria.

• Collaborate on design efforts using Figma when user interface elements are involved.

• Maintain documentation of feature decisions and ensure a shared source of truth is available.

• Establish quality standards, rubrics, evaluations, annotation standards, and human-data quality processes.

• Engage with customers and domain experts, integrating Post Sales Support and AI Labs Services Delivery into the planning process.

• Ensure alignment among engineering, product, research, sales, policy, legal, data science, and delivery teams.

• Guide both in-progress and new features through the phases of building, demonstration, launch, and follow-up.

• Review recordings and work collaboratively with GTM on discovery and translating technical product capabilities during both pre-sales and post-sales.

• Assist in defining how product management evolves as the platform and team expand.

⛳️ Requirements

• A minimum of 7 years of experience as a technical product manager, technical program manager, or product-focused engineer in software, data, or AI platform development, managing features from requirements to production.

• Sufficient technical understanding to read and reason about code, system design, and data models, enabling informed trade-off decisions.

• Proven experience in defining technical contracts, including APIs, data schemas, evaluation metrics, and acceptance criteria.

• Experience shipping at least one evaluation or benchmarking system, red-team or safety-testing tools, annotation or labeling pipelines, or datasets and data-processing platforms.

• Proficiency with the modern AI application stack, including LLM orchestration, retrieval, evaluation pipelines, and monitoring tools.

• Familiarity with delivery tools such as version control, feature flags, continuous integration, and issue trackers like Linear.

• Preferred experience in high-stakes or regulated domains such as Trust & Safety.

• Preferred experience in transforming taxonomies and rubrics into measurable, repeatable evaluation workflows.

• Preferred knowledge of reinforcement learning environments, reward modeling, or agent evaluation harnesses.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and continuous learning.

• A collaborative and innovative work environment.