Sr. Staff Technical Product Manager

Groq•Worth, IL

3h•$310,400 - $365,200

About The Position

Groq is seeking a Sr. Staff Technical Product Manager to shape its AI inference platform by owning product strategy and execution for critical platform areas. The role turns complex infrastructure challenges into scalable, reliable, and intuitive product experiences that help developers and enterprises build AI applications at scale. Working at the intersection of AI infrastructure, cloud technology, and distributed systems, the product manager partners with Engineering and cross-functional teams to define and deliver platform capabilities. The position has hands-on ownership of products from concept through launch and continuous improvement, and influences product direction across the platform. The role must be based in the Dallas, San Francisco, or New York City area. Remote work is available while Groq establishes a local office, with the expectation that the position will transition to onsite once the office opens.

Requirements

10 or more years of Product Management experience, including at least 5 years leading highly technical platform, infrastructure, or cloud products.
Deep domain expertise and demonstrated ownership of technically complex products in AI inference, cloud infrastructure, or related environments such as inference engines, LLM serving platforms, neoclouds, or AI cloud services.
Strong understanding of distributed systems, cloud infrastructure, APIs, Kubernetes, observability, platform reliability, capacity planning, and multi-region architectures.
Proven ability to independently define and deliver complex technical products, including developing specifications, prioritizing features, and driving execution with engineering teams.
Strong technical judgment and experience partnering with senior engineering leaders to translate customer needs into product strategy, influence architectural decisions, and deliver scalable infrastructure capabilities.
Self-directed, comfortable navigating ambiguity, making decisions, and driving progress with minimal oversight.
Strong analytical and problem-solving skills and a data-driven approach to prioritization and decision-making.
Excellent written and verbal communication skills, including the ability to influence engineering teams, cross-functional stakeholders, and executive leadership.
Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Nice To Haves

Familiarity with infrastructure utilization, fleet scheduling, capacity forecasting, cloud economics, and platform operations.
Experience with consumption-based cloud services for enterprise customers, AI accelerators, or hardware and system bring-up.

Responsibilities

Drive product definition and delivery by translating customer needs, technical constraints, and business priorities into specifications, feature requirements, success metrics, and execution plans from concept through launch and continuous improvement.
Apply AI infrastructure and cloud platform expertise to platform initiatives, contributing to technical specifications, architecture discussions, and roadmap priorities across multiple workstreams.
Partner with Platform Engineering, Distributed Systems, Cloud Infrastructure, Reliability Engineering, Hardware Engineering, and customer-facing teams to deliver scalable, reliable, customer-centric platform capabilities.
Work with engineering leadership to navigate technical tradeoffs and balance customer impact, technical investments, platform scalability, and long-term architectural evolution.
Shape customer-facing cloud capabilities, including inference APIs, developer workflows, and platform experiences, to make infrastructure services easier to adopt, deploy, and scale.
Define and prioritize internal platform investments in cloud infrastructure, resource management, observability, and platform optimization to improve scalability, reliability, operational efficiency, and infrastructure utilization.
Lead customer discovery with enterprise AI customers and developers to understand workloads, deployment workflows, performance expectations, operational challenges, and emerging infrastructure needs.
Measure product adoption, customer experience, and platform performance using customer feedback, telemetry, and operational metrics, and use findings to improve customer outcomes.
Collaborate with Sales, Solutions Engineering, Customer Success, and Marketing on product launches, customer adoption, and go-to-market initiatives.
Monitor the AI inference and cloud infrastructure landscape for emerging technologies, customer needs, and product differentiation opportunities.
Communicate product strategy, roadmap, priorities, risks, and progress to executive leadership and cross-functional stakeholders.