Staff Platform Engineer (Pacific Time Zone)

Responsibilities

• Own and deliver major subscription service initiatives (e.g., My Subscriptions enhancements, self-service SAML SSO, new admin workflows) to improve time-to-onboard and operator efficiency
• Architect and deploy custom MCP (Model Context Protocol) tooling and autonomous agents for seamless data interoperability between internal systems and AI models
• Contribute to development of secure, reliable API endpoints and platform services to make platform infrastructure highly reliable, easy to maintain, and cost-effective
• Define and improve monitoring, alerting, and observability for platform services; participate in on-call rotation
• Act as escalation point for complex, cross-system incidents touching KMC, Connector, and App Builder
• Collaborate with solution architects, forward-deployed engineers, customer success, and product teams to support new feature rollouts and integrate authentication services
• Implement measures to enhance developer experience including well-documented code, clear API documentation, efficient debugging tools, and adoption of AI-powered development workflows (Cursor, Claude, Gemini)

Requirements

• Expert-level backend engineering experience (Python + FastAPI preferred) building and operating APIs and microservices at scale with strong debugging and technical troubleshooting skills
• Proven track record designing and evolving core platform primitives (authentication/authorization, orgs/accounts, subscriptions, or similar control-plane systems) in a multi-tenant SaaS environment
• Profound experience with AWS core services and ability to architect secure, scalable, and cost-efficient solutions
• Familiarity with modern data platforms and workflow tools (Snowflake, Airflow, Spark) and understanding of observability (metrics, logs, traces, events) across complex distributed systems
• Ability to design solutions balancing performance, cost, maintainability, reliability, and developer experience
• Demonstrated ability to drive complex, cross-team projects, mentor engineers, and collaborate with product managers, data scientists, and customer-facing teams
• Comfort leveraging AI tools (Cursor, ChatGPT, Gemini) and interest in integrating LLM-based workflows into the SDLC

Nice-to-Haves

• AWS cloud infrastructure certification
• Experience with data privacy concerns such as HIPAA or GDPR
• Working knowledge of data modeling and storage across relational (PostgreSQL), NoSQL (DynamoDB, Redis), and MPP databases (Snowflake, Redshift)
• Prior experience in platform or infrastructure teams supporting internal and external developers, including SDKs, CLIs, and self-service tooling