Senior Fullstack Engineer - Product Platform Engineering

Pivotal Health•Los Angeles, CA

1d•$190,000 - $220,000

About The Position

The product platform is the layer other product teams build on. Today that means identity and access, including customer SSO, invitations, and sessions; the organization and tenancy model; the shared services, APIs, and schemas that carry customer data between products; and the developer experience, including the tooling and agent workflows engineers use to ship. The scope grows whenever product teams need a capability that should be built once. Role-based access control, email infrastructure, the production path for the models our products depend on, and likely data ingress are next in line. When this layer is right, product teams move faster and customers have a better experience. This role is for engineers who think deeply about systems and can explain why a solution works as well as how to build it. You'll own components and services within the platform end to end, partner closely with product engineering, data, and infrastructure teams, and make the architectural decisions that keep the platform reliable and extensible as the business takes on more customers and more complexity. Expect us to ask about a system you built: who used it, why they cared, and what you would have built differently had you understood that sooner.

Requirements

5+ years of experience in fullstack, backend or platform software engineering
Strong software engineering foundation with solid coding skills; Python preferred
Hands-on experience designing and operating cloud-native systems; GCP preferred
Experience with relational databases and data modeling, including schema evolution in production
Familiarity with event-driven architectures (Kafka, Pub/Sub, Kinesis, or similar)
Range to move between domains such as authorization, messaging infrastructure, and data pipelines without needing each to be familiar first
Strong product instincts: you judge a system by whether it is useful and correct, and elegance comes second
You want to know why a customer cares before you build, and you go find out: from product, from support, from the customer directly
Self-directed and proactive: you identify problems and drive them to resolution without heavy oversight
Comfortable in greenfield environments with evolving requirements and ambiguous ownership
Low-ego and collaborative by default: direct, open to feedback, and more interested in shipping great work than in being right

Nice To Haves

Identity and access systems (OIDC, SAML, SSO, sessions) or authorization models such as RBAC
Transactional email or messaging infrastructure, including deliverability and bounce handling
Data ingestion pipelines, or the tooling that moves ML models from experiment to production
Internal libraries, SDKs, or developer tooling that other teams adopted
Automation or AI-assisted tooling that reduced operational toil
TypeScript and React, enough to work across the products the platform serves
Startup or early-stage experience where engineers own outcomes rather than tickets
FinTech, HealthTech, or other regulated industries

Responsibilities

Own platform components end to end: Design, build, and operate services, libraries, and schemas within the platform, from design through production, with clear ownership of their reliability and evolution.
Design for extension and reuse: Build composable abstractions and well-defined interfaces so product teams can extend the platform without forking it or waiting on you.
Design scalable, reliable system interactions: Contribute to the design of system interactions and data flows, making architectural decisions that balance scalability, reliability, security, and performance as the platform evolves.
Improve reliability and operational signal: Build and evolve monitoring, alerting, dashboards, and testing pipelines that surface meaningful signal rather than noise.
Reduce toil: Identify repeating patterns across teams and make them composable through better abstractions or new tooling, including AI-assisted tooling where it helps.
Partner with product teams: Work as an embedded partner to feature teams, unblock delivery, and make sure platform decisions reflect what those teams actually need.