Job Description A growing technology company is developing an AI-powered platform that connects software, scientific models, data, and experimental workflows to help research teams move from questions to real-world results. The company works at the intersection of artificial intelligence, advanced computing, and physical science, with a focus on making complex research processes more coordinated, traceable, and effective.
As a Technical Product Manager - Software and Agents, you'll own the agentic and core software layers of the platform. You'll shape how users define research goals, how AI agents plan and carry out work, and how the platform uses experimental results to improve future decisions. You'll work closely with software engineers, machine learning researchers, and scientists, translating customer and research needs into a coherent product.
This is a hands-on product ownership role, not a coordination position. You'll set the roadmap for shared software, data, and infrastructure; decide what capabilities belong in the core platform; and guide the path from research prototype to production. You'll establish what makes a capability useful and reliable enough to deploy, while making decisions and earning alignment across teams with deep technical expertise and strong perspectives.
This is a full-time, onsite position based in Brooklyn, NY. You'll report to a senior company leader and help define the product direction for a platform where established product-management playbooks may not yet exist.
Required Skills & Experience - 5-7 years of product management experience, including at least 1 year working on products built around AI agents or machine learning
- Experience at a technical or deep-technology company
- Technical credibility, including the ability to read code, build lightweight prototypes, and reason about agent architectures, APIs, data flows, and integrations
- Ability to work through technical feasibility and tradeoffs directly with engineers and researchers
- Strong judgment about the limits and appropriate uses of AI agents, including tool reliability, error propagation, grounding, evaluation, and human oversight
- Experience connecting offline model and agent metrics to real customer or operational outcomes
- Ability to bring agents, models, user experience, and platform foundations together into a coherent product
- Proven ability to set priorities and build alignment across engineering, research, science, and design teams
- Strong first-principles thinking and comfort creating structure in ambiguous environments
Desired Skills & Experience - Experience with scientific software, such as materials science, chemistry, physics-based simulation, or surrogate models for computationally expensive work
- Familiarity with Bayesian optimization, active learning, or closed-loop experimentation
- Experience with DevOps, MLOps, or data platform products
- Exposure to enterprise customers
What You Will Be Doing Daily Responsibilities
- Own the roadmap for the shared software, data, and infrastructure that supports the platform's agents, models, and laboratory systems
- Define what belongs in the core platform, what should remain at the edges, and what should be built versus adopted
- Guide the development of core services and APIs for workflow orchestration, experiment and sample records, data access, and coordination between agents, models, and laboratory systems
- Shape how research, simulation, and literature data are captured, structured, versioned, and made usable
- Set expectations for reliability, performance, observability, security, and readiness for production
- Define what agents can do, which tools and services they can use, and where human review or approval is needed
- Design how users set research goals, review agent plans and decisions, and trace results back to their underlying data, models, and experiments
- Establish metrics, benchmarks, and acceptance criteria that reflect improvements in laboratory and customer outcomes
- Guide decisions about how predictive and generative models are served, versioned, and monitored, including whether to build, fine-tune, or adopt models
- Improve the learning loop between model outputs, experiment design, and experimental results
- Shape the interfaces through which scientists and customers use the platform and receive results, including APIs, data exports, and reports
- Define data-governance requirements, including customer data separation, data rights, and the handling of export-controlled information
- Set and measure customer commitments, ensuring product claims are clear and appropriately scoped
- Partner with the product manager responsible for robotics and autonomy to define the interface between the core platform and physical laboratory systems
- Coordinate with partner and customer product teams on data formats, requirements, and priorities
- Communicate product direction to engineering and research teams, as well as company leadership
The Offer - Compensation of $170,000-$220,000 per year
- Full-time, onsite work in Brooklyn, NY
- Opportunity to shape the roadmap and product standards for an emerging AI and scientific-computing platform
- Direct collaboration with software engineers, machine learning researchers, and scientists
- Ownership of the product path from research prototype to production
