Principal Product Manager, AI

Highspot•Seattle, WA

46d

About The Position

In this role, you will be joining the Product Management team reporting to the Director of Product Management in our AI Platform Pillar. The Product Management function at Highspot is an integral part of the company. You will be jumping into many different projects and features, and will be very hands-on. You will be working very closely with a senior engineering team and experienced design partners. Over time, you will have the opportunity to help shape and grow not just the product, but also the team. We're hiring a Principal Product Manager to lead the strategy, execution, and evangelism of AI-first product initiatives that deliver clear customer value at scale. You'll define the vision and roadmap for a major AI capability - from model selection and data strategy to product UX, and additional platform capabilities- and partner closely with engineering, research, design, GTM and legal to ship safe, reliable, and differentiated AI experiences. This role carries the Principal PM level of ownership: you'll set strategy across an area of the product portfolio, lead cross-functional feature crews, and raise the bar for product craft and technical rigor. Our ideal candidate is someone who enjoys understanding a broad set of customer requirements, digging into technical constraints, and using their expertise to deliver an elegantly simple customer experience. This person will benefit from being a skilled communicator, who can drive enterprise-level customer conversations, collaborate effectively with other disciplines, and land proposals with stakeholders.

Requirements

This is a principal-level position. You have been building software products for some time and have 8+ years of experience shipping products as a PM.
You are experienced at taking ideas and ambiguous data, defining the right outcome, and then mapping the right roadmap/backlog to get there.
You are able to consider and balance the many different data points and opinions about your area of ownership.
You can communicate and articulate the strategy and roadmap to execs, team members and customers.
This is a technical role, you will be able to work directly with senior engineers and instinctively understand technical concepts and trade-offs.
You are able to comfortably handle many concurrent projects and todo's, and instinctively re-prioritize often without needing guidance. Highspot is in a high growth stage and you will be comfortable with the level of ambiguity and workload that entails.
You have worked with engineering teams as a product owner and have demonstrable experience leading cross-functional teams to ship high-quality products.
You have the ability to roll up your sleeves and pick up work outside of your role definition when you need to. You are a strong communicator and can lead teams through difficult decisions.
You have strong data skills in quantitative analytics and qualitative user research.
8+ years product management experience building B2B SaaS products; 4+ years working directly with ML/AI products or platforms.
Demonstrated technical fluency with modern generative AI / ML concepts (LLMs, RAG, embeddings, vector DBs, fine-tuning, prompt engineering, evaluation metrics, model ops). You don't have to be an ML engineer, but you must confidently discuss architectures, tradeoffs, and productionization.
Proven record of shipping complex, cross-functional AI products or platforms to production and driving measurable business impact.
Strong quantitative and analytical skills - comfortable defining metrics, designing experiments, and using data to validate hypotheses.
Exceptional communication skills: you can write crisp specs, present tradeoffs to executives, and explain technical topics to non-technical audiences.
Experience mentoring PMs and participating in hiring; a track record of raising the bar for product craft.

Nice To Haves

Background building platform or infrastructure used by other product teams (e.g., model-serving, feature stores, observability, inference cost management).
Experience with search & recommendation systems or agents/assistants at scale. (Experience here is especially valuable if the role sits on Agents or Search teams.)
Experience with enterprise customers, sales enablement workflows, and integrating AI into product flows that serve customer-facing teams.
Familiarity with safety, policy, and compliance workstreams (content policies, PII handling, incident response).

Responsibilities

Define vision & strategy. Set the long-term product vision and multi-quarter roadmap for Highspot AI capabilities (e.g., model evaluation/monitoring, orchestration, entity detection, recommendation systems, observability, etc.). Translate company goals and customer needs into prioritized opportunities and measurable outcomes.
Lead execution end-to-end. Drive discovery, product design, technical scoping, and delivery with a feature crew of engineers and designers. Make trade-offs to ensure speed and quality while keeping long-term platform health in mind.
Own model + product success. Define model and product metrics, experimentation strategy, and SLA/quality targets. Partner with engineers and research to evaluate architectures (LLMs, RAG, retrieval, embeddings), set up model evaluation pipelines, and operationalize model monitoring and feedback loops.
Drive platform & scale thinking. Design solutions that are performant, cost-aware, secure, and easy for other product teams to adopt. Where relevant, define APIs and tools, data contracts, and telemetry to support product and model lifecycle management.
Champion safety, fairness & compliance. Establish guardrails, prompt / output validation, content filters, and incident playbooks. Work with Legal and Security to ensure data privacy and regulatory compliance.
Be the cross-functional glue. Work closely with design, research, engineering, SRE, data science, analytics, sales engineering, and GTM to launch and scale features. Translate technical tradeoffs into business tradeoffs for executives and stakeholders.
Mentor & raise the bar. Coach other PMs, participate in hiring, and help define best practices for ML product management and technical specwriting.