Senior Product Manager Platform

SnapLogic•San Mateo, CA

5d•$190,000 - $215,000•Hybrid

About The Position

SnapLogic is seeking a Senior Product Manager to own the strategy and roadmap for its core platform. This platform is the engine that powers the entire business, encompassing the control plane, data plane, and observability layer. The role involves treating the platform as a product with internal teams and external developers as customers, ensuring it delivers reliability, scalability, security, and generative/agentic capabilities. The Senior Product Manager will report to the VP of Product Management and champion a "platform-as-a-product" philosophy. Success will be measured by customer-experienced reliability and performance, the speed at which product teams can build on the platform, its support for new generative and agentic workloads, smooth operation in various deployment models, and cost-efficiency. This is a hybrid position based at SnapLogic's HQ in San Mateo, CA.

Requirements

Proven platform expertise. 5+ years of product management in B2B SaaS, with significant focus on platform, infrastructure, PaaS, or API-centric products.
Deep technical fluency. You can hold your own in discussions about distributed systems, runtime/execution engines, microservices, data pipelines, and API design, and engage senior engineers as a credible partner. (A computer science degree is not required — relevant hands-on depth matters more.)
Runtime and deployment depth. Experience with products that run across more than one deployment model — multi-tenant cloud, hybrid, or on-premises / agent-based — and an understanding of the trade-offs each imposes.
Observability mindset. Familiarity with telemetry, monitoring, alerting, and SLO/SLI-driven operations, and an appreciation for the operator and administrator experience.
Fluency in the AI/agentic landscape. A working understanding of how AI agents, LLMs, and protocols like MCP run on top of infrastructure, and a genuine interest in building the platform that makes generative integration possible. (You'll partner with the AI PM — you don't need to be the AI expert, but you should be conversant.)
Enterprise-grade experience. A strong understanding of the security, reliability, and scalability requirements of Global 2000 customers, and a track record of shipping products that meet them.
Business-savvy strategist. Experience building business cases, partnering with GTM teams, and linking platform investment to business outcomes and ROI.
Customer-obsessed leader. A deep commitment to understanding and solving the real needs of your customers — internal teams, external developers, and the operators who run the platform.

Nice To Haves

Direct experience with application integration platforms (iPaaS), business systems integration, or API-led connectivity.
Experience with observability or monitoring products, or with platform reliability / SRE-adjacent collaboration.
Experience with hybrid-cloud or agent-based deployment models in regulated or security-sensitive enterprises.
Experience building or operating infrastructure for AI/ML or agentic workloads — for example, supporting LLM-based applications, AI agents, or MCP servers in production.
An entrepreneurial streak — taking products from concept to launch in ambiguous environments.
Comfort acting as a product evangelist with technical audiences, customers, and at industry events.
A blend of high-growth startup and large at-scale technology company experience.

Responsibilities

Own the platform vision. Define, evangelize, and execute a multi-year vision and roadmap for the core platform, and drive alignment across engineering, product, and executive leadership so it serves the broader business strategy.
Own the control plane. Set the direction for how the platform is managed, orchestrated, configured, and governed — including configuration and lifecycle management, safe rollout mechanics (versioning, phased rollouts, rollback), multi-tenancy, and the security and governance controls enterprises require.
Own the data plane. Drive the runtime that executes customer workloads — its performance, throughput, and resilience — across cloud-hosted, hybrid, and on-premises deployment models, including how runtime engines deploy inside customer environments and scale under enterprise load.
Own observability. Make the platform measurable and debuggable for the people who operate it. Drive the strategy for telemetry, monitoring, alerting, and SLOs/SLIs, and for the self-service troubleshooting experience that lets customers and internal teams resolve issues quickly.
Enable generative integration. Ensure the platform is the foundation on which AI agents and MCP servers run reliably and at scale. Partner with the AI product manager to translate the product's generative and agentic roadmap into the underlying platform capabilities it depends on.
Champion the developer and operator experience. Obsess over the end-to-end journey for the people who build on and run the platform. Drive the strategy for APIs, SDKs, and documentation to create a world-class, self-service experience.
Tie investment to outcomes. Author business cases that connect platform investments to measurable results — faster GTM for new products, infrastructure cost-efficiency, and improved customer satisfaction and retention.
Set and defend KPIs and SLOs. Partner with Principal Engineers on architecture decisions across microservices, data models, and APIs, and define the KPIs and service-level objectives that hold the platform to an enterprise-grade reliability bar.
Prioritize and make trade-offs. Own the roadmap and backlog, and make the hard prioritization calls that keep engineering focused on the highest-impact work.
Lead through influence. Guide cross-functional teams through the full lifecycle — discovery, experimentation, launch, iteration — and build a culture of data-driven decision-making.
Be the platform's advocate. Communicate the platform's value and direction to internal stakeholders, partners, and the market through clear writing, presentations, and thought leadership.