About Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
The Role:
We are looking for a Technical Product Manager to own the roadmap and execution across Snorkel AI's Infrastructure organization, spanning three engineering pods: Core Services, Developer Experience, and Security. This is not a customer-facing product role, you will be the PM for internal platforms, data infrastructure, and security systems that the rest of engineering and the business depend on. You will be the single point of coordination across a broad surface area that currently lacks dedicated product leadership.
What You Will Do:
The Infrastructure org owns the data platform, event systems, observability, developer tooling, release pipelines, and the full security stack. The engineering leadership and pod leads are very technical but the org needs a PM who can translate business and compliance requirements into prioritized infrastructure investments, manage dependencies across pods and partner teams, and hold the line on scope and delivery timelines. Today, prioritization decisions are made ad hoc by engineering leads who are also deep in technical execution. This role gives the org a dedicated owner for roadmap clarity, stakeholder alignment, and cross-pod coordination.
Business context and infrastructure strategy:
- Develop a deep understanding of Snorkel AI's business, how the datasets are sold, and how should the platform be deployed, and scaled to support customers across AI labs, enterprise and federal and use that context to work closely with engineering leaders and product PMs to translate business scaling, security and functional needs into deployment patterns, and go-to-market requirements into concrete, prioritized projects for the Infrastructure org. Without this, infrastructure roadmaps become technically interesting but disconnected from what actually moves the business forward.
Roadmap and prioritization across all three pods:
- Work with engineering leads to define quarterly roadmaps for Core Services (data platform, metrics platform, event systems, observability, fraud detection, infrastructure cost management, platform customization infrastructure, SDS project infrastructure), Developer Experience (CI/CD, release pipelines, dev systems, AI dev tooling), and Security (Auth0 migration, AuthN/AuthZ, cloud security, encryption).
- Make trade-off decisions when pods compete for shared resources or when new asks land mid-quarter. The org carries significant surface area relative to headcount. Your job is to ensure the team is working on the highest-leverage problems, not just the loudest requests.
Stakeholder management and requirements gathering:
- Be the interface between the Infrastructure org and its consumers: product engineering teams who depend on Dataset APIs, Platform APIs, and Packaging APIs; the data science and analytics teams who depend on Cascade and the transformation layer; GTM and customer success teams who surface compliance and security requirements from enterprise and federal customers.
- Translate customer compliance requirements (SOC 2, FedRAMP, GDPR) into concrete security and data governance work items with clear acceptance criteria.
Adoption and internal evangelism:
- Proactively engage product PMs and engineering leads to ensure teams are leveraging infrastructure services, SDKs, and shared libraries (unified data access, event bus, security SDKs, CI/CD tooling) rather than building one-off solutions.
- Track adoption metrics, SDK integration coverage, service onboarding rates, migration completions, and identify teams that are lagging or working around infrastructure offerings. Close the loop by either driving adoption or feeding unmet requirements back into the roadmap.
- The Infrastructure org's impact is only as real as its adoption. You own the push to make sure the work doesn't just ship, it lands.
Cross-pod coordination on foundational initiatives:
- Drive initiatives that span multiple pods, such as the unified data access library (which touches Core Services for the library itself, Security for auth/RBAC/encryption enforcement, and Developer Experience for SDK distribution and testing tooling).
- Coordinate the event bus rollout across services, ensuring schema governance, consumer onboarding, and observability are sequenced correctly.
- Own the Auth0 migration program as a cross-functional deliverable that touches Security, Core Services, and every API team.
Metrics, reporting, and visibility:
- Define and track key metrics across pods: data platform query latency, event bus propagation latency, CI pipeline duration, release rollback rate, security finding remediation time, encryption coverage, infrastructure cost per workload.
- Provide regular reporting to VP-level leadership on infrastructure org health, delivery status, and risk areas.
- Maintain a clear view of staffing gaps and make the case for headcount investments backed by roadmap impact.
Infrastructure cost and efficiency:
- Partner with Core Services on infrastructure cost visibility, attribution, and optimization. Own the narrative around infrastructure spend not just tracking it, but driving decisions on reserved capacity, right-sizing, and cost allocation by team and product.
- Own inference cost management as a cross-functional concern that touches both infrastructure and product economics.
Minimum Qualifications:
- 7+ years of product management experience, with at least 2 years in infrastructure, platform, or developer tools PM roles. You have shipped internal platforms or infrastructure products, not just customer-facing features.
- Strong technical fluency. You don't need to write Terraform modules, but you need to understand what an event bus is, why CDC lag matters, what RBAC enforcement means at the data layer, and why audit logs shouldn't live in the production database. You can hold your own in architecture discussions and push back on technical proposals with substance, not just process.
- Experience with compliance and security programs. You have worked on SOC 2, FedRAMP, or similar compliance frameworks and understand how to translate audit requirements into engineering work items. You know the difference between checking a box and actually being secure.
- Comfort with ambiguity and breadth. This role covers platform infrastructure, data infrastructure, developer tooling, and security, three domains that each could be a full-time PM role at a larger company. You are comfortable context-switching, prioritizing ruthlessly, and saying no to work that doesn't clear the bar.
- Experience working with small, high-leverage engineering teams.You understand that with small teams, every quarter's roadmap is a zero-sum game, and your job is to make sure the bets are right.
- Fluency with AI-assisted workflows is a plus. The org treats AI tooling (Claude Code, Cursor) as a baseline expectation for engineers; a PM who understands and can evaluate these tools' impact on developer productivity will be more effective in this role.
Preferred Qualifications:
- 7+ years of experience as a Product Manager, including 3+ years focused on ML/AI products, MLOps, Platform infrastructure or data systems products.
- Experience with agent-based systems, generative AI, reinforcement learning, self-improving systems, or automated workforce/task routing platforms.
- Familiarity with LLMs, LLM Evaluations, human-in-the-loop systems, and synthetic data generation.
- Background in Computer Science, Security or related technical field.
- Demonstrated ability to lead large, cross-team initiatives without formal authority.
Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.
Salary range(s) for this role
$220,000—$280,000 USD
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
