Technical Product Manager

Job description

About mpathic mpathic is building the future of trustworthy AI. Grounded in behavioral science and human-centered design, we provide the infrastructure for building AI systems that are safe, aligned, and emotionally intelligent. Building on our work in areas like RL gyms, red teaming, and benchmarking, we are creating the foundation for training, probing, and measuring advanced AI systems reliably, auditably, and at scale. Position Overview We are looking for a Technical Product Manager to turn mpathic's platform vision into shipped product. You will sit on the platform team, reporting to the CTO, and act as the connective tissue between engineering, the Head of AI Product, research, sales, and the teams who deliver to customers. You will own how a feature moves from idea to launch: framing the problem, writing clear requirements, coordinating design and engineering, running demos for feedback, and guiding the work to a confident release. Our platform spans red teaming, dataset generation, annotation, and evaluation, much of it in high-stakes domains where quality and auditability matter. Your job is to translate ambiguous customer, clinical, and operational needs into precise product requirements and dependable delivery, and to keep the many people involved aligned around what we are building and why. This is a role about both definition and delivery. You should be as comfortable talking to customers and domain experts and writing a crisp spec as you are sitting with engineers to sequence the work and unblock it. You will start as a hands-on individual contributor and the single owner for the features you shepherd, with room to shape how product management works here as the team grows. What You'll Do Own Feature Delivery, Idea to Launch (Core) Be the single owner for the platform features you shepherd, carrying each from intake through scope, build, demo, and launch. Decide, with the CTO and Head of AI Product, what is ready to build, and keep the plan and its rationale clear for everyone involved. Run the demo and feedback cadence, capture feedback in Linear, and keep scope honest as the work evolves. Translate Needs into Requirements & Specs Turn validated direction into precise product requirements, with explicit scope, non-goals, and one clear success metric per feature. Partner on design (Figma where there is UI) and write acceptance criteria engineering can build against. Document the decisions that hold a feature together, so nothing important lives only in someone's memory. Define Quality, Evaluation & Annotation Standards Define what “good” means for the features you own, and the rubrics and evaluations that measure it. Set annotation and human-data quality standards that are consistent, auditable, and humane for the people doing the work. Capture Inputs from Customers & Delivery Talk to customers and domain experts, and bring the front-line delivery teams (Post Sales Support and AI Labs Services Delivery) into planning on purpose. Turn what you learn into roadmap candidates rather than one-off workarounds. Be the Connective Tissue Keep engineering, the Head of AI Product, research, sales, and delivery aligned on what is being built and why. Translate between technical, clinical, and commercial perspectives so the right tradeoffs get made. What You'll Accomplish In your first 60-90 days you'll… Build a deep understanding of the platform, its users, and the high-stakes domains it serves, and a clear picture of how work flows from idea to launch today. Take ownership of one or two in-flight features, write or sharpen their requirements, and shepherd them through build and demo to launch. Establish a lightweight, shared way of writing requirements and capturing decisions in Linear, so the team has one source of truth. Build trusted relationships across engineering, the Head of AI Product, research, sales, and the delivery teams. In your first year you'll… Own the end-to-end delivery of platform features on the full path, from requirements through launch and follow-up, in partnership with CTO and Head of AI Product. Turn validated direction from the Head of AI Product and research into precise PRDs, designs (with Figma where there is UI in partnership with design), and clear acceptance criteria. Stand up the rubrics, evaluation, and annotation-quality standards that make platform outputs trustworthy and auditable for internal teams and customers. Build a dependable feedback loop with the front-line delivery teams (Post Sales Support and AI Labs Services Delivery) so their needs reach the roadmap. Review recordings, collaborate with GTM org for discovery and translation of technical product capabilities throughout the pre-sales and post-sales process. Help define how product management scales at mpathic as the platform and team grow. You'll Thrive in This Role If You… Translate ambiguity into clarity: you can take a messy customer, clinical, or operational need and turn it into a precise requirement, a clear spec, and a plan engineers can build against. Bring an evidence-based, rigorous approach, ideally grounded in behavioral or social science, and care deeply about reliability, reproducibility, and auditability. Have designed taxonomies, rubrics, evaluations, or annotation workflows, and understand what it takes to make human-data and quality processes trustworthy at scale. Understand modern AI evaluation and red teaming concepts (for example jailbreaks, prompt injection, policy probing, and evaluations used as a quality signal) and how to operationalize them into repeatable, measurable workflows. Are comfortable with high-stakes, sensitive subject matter such as safety, wellbeing, and risk domains, and bring care for both users and the teams doing the work. Communicate crisply through structured writing, specs, and diagrams, and can align people around a direction without relying on authority. Are energized by being the connective tissue across engineering, product, research, policy, legal, data science, and customer-facing teams. Have shipped real products or programs in complex technical environments, shown through what you have delivered rather than years on a résumé. Experience in Trust & Safety, responsible AI, or applied research is a strong plus. Experience Core experience 7+ years as a technical product manager, technical program manager, or product-minded engineer building software, data, or AI platforms, owning features from requirements through production. Technical depth to be a credible peer to engineers: you can read and reason about code, system design, and data models well enough to weigh tradeoffs, even if you do not write production code day to day. A track record of defining a product's technical contracts: APIs, data schemas, evaluation metrics, and acceptance criteria that engineering can build against. Shipped at least one of: an evaluation or benchmarking system, red-team or safety-testing tooling, an annotation or labeling pipeline, or a dataset or data-processing platform. Working fluently with the modern AI application stack (LLM orchestration, retrieval, evaluation pipelines, and monitoring) and the delivery toolchain (version control, feature flags, CI, and an issue tracker such as Linear). Preferred Experience in high-stakes or regulated domains such as Trust & Safety, where auditability and rigor are required. Experience turning taxonomies and rubrics into measurable, repeatable evaluation workflows in software. Familiarity with reinforcement-learning environments, reward modeling, or agent evaluation harnesses. About the Team You will work closely with: CTO and platform engineering: to scope, sequence, and ship the work. Head of AI Product, Chief Science Officer and Research Team: to turn validated direction and scientific requirements into shippable product. Domain experts: to ground the work in real practice and quality of findings. Sales and the delivery teams (Post Sales Support and AI Labs Services Delivery): to align what we build with customer needs and deliverables. Apply Even If You Don’t Check Every Box If you’re excited about bringing operational excellence, systems thinking, and high standards for quality, clarity, and auditability - we’d love to hear from you.