Senior Staff Digital Platform Engineer

Revolution Medicines•Redwood City, CA

10h•$186,000 - $233,000•Hybrid

About The Position

Revolution Medicines is seeking a Senior Staff Digital Platform Engineer to help build and scale the common digital platform, engineering practices, and enablement model that allow teams across Information Sciences, R&D, and business functions to create trusted digital applications faster and more consistently. This role focuses on scaling how digital products are built across the enterprise. You will work with other Staff Engineers to develop digital products, design reusable platform capabilities, shared services, reference architectures, engineering standards, and developer enablement programs that help domain teams build applications on top of RevMed's data and AI platform. You will also establish trustworthy patterns for AI-native and agentic engineering so AI-assisted and agent-based applications are secure, reliable, auditable, maintainable, and production-ready. This is a cross-functional technical leadership role, partnering with Information Sciences, R&D, Data Product Management, Data Engineering, Platform Engineering, Security and business stakeholders.

Requirements

12 - 15+ years of experience in software engineering, digital product engineering, platform engineering, enterprise architecture, or related technical roles.
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent professional experience.
Experience operating at a Senior Staff, Principal Engineer, Architect, Associate Director, Engineering Director or equivalent technical leadership level.
Proven experience designing and delivering production-grade digital applications, developer platforms, shared services, or reusable engineering frameworks.
Strong hands-on engineering background across backend services, APIs, distributed systems, cloud-native architectures, and modern frontend patterns.
Experience building or enabling full-stack digital products that integrate data, workflow, AI/GenAI, APIs, and user-facing interfaces.
Practical experience with AI-native application patterns such as RAG, LLM integration, agent orchestration, workflow automation, validation pipelines, and human-in-the-loop systems.
Strong understanding of platform engineering concepts, including golden paths, self-service capabilities, reusable components, developer experience, paved roads, and automated guardrails.
Experience defining architecture standards, system design patterns, and engineering practices adopted by multiple teams.
Knowledge of domain-driven design, test-driven development, automated testing, CI/CD, production readiness, observability, and secure SDLC.
Experience with AWS and/or Azure.
Ability to collaborate with Information Sciences, R&D, business stakeholders, Security, Architecture, Data Engineering, Platform Engineering, and Product Management.

Nice To Haves

Experience in biotechnology, pharmaceutical R&D, life sciences, clinical development, regulatory, medical writing, or another regulated environment.
Experience building platforms or applications for scientific, research, clinical, regulatory, or enterprise business teams.
Experience with Databricks, Spark, Delta Lake, dbt, lakehouse architectures, vector databases, embeddings, feature stores, or semantic layers.
Experience with API management, event-driven architecture, workflow orchestration, data integration, and enterprise interoperability.
Experience establishing developer enablement programs, internal platforms, engineering academies, communities of practice, or technical coaching models.
Experience mentoring senior engineers, leading architecture forums, or defining standards across multiple teams.

Responsibilities

Build and Scale Digital Platform Capabilities: Design reusable platform capabilities, shared services, components, application templates, reference implementations, and golden path patterns for digital product development.
Define architecture patterns for backend services, APIs, frontend applications, workflow orchestration, data access, identity/access management, auditability, observability, and deployment.
Partner with platform, cloud, security, and architecture teams to ensure digital applications are secure, scalable, maintainable, and aligned with enterprise standards.
Standardize common patterns for authentication, authorization, logging, monitoring, notifications, workflow services, data access, environment management, and CI/CD.
Build communities of practice around modern software engineering, AI-native development, domain-driven design, test-driven development, and platform usage.
Establish Trustworthy AI and Agentic Engineering Practices: Define standards and guardrails for AI-assisted and agentic application development.
Create reusable patterns for RAG, LLM integration, agent workflow orchestration, prompt/tool design, validation workflows, human review, evaluation harnesses, telemetry, and AI observability.
Establish quality gates for AI-assisted software, including automated testing, code review, security checks, architectural review, observability, and production-readiness requirements.
Partner with Security, Privacy, QA/Validation, Architecture, and Information Sciences to define appropriate controls for regulated or sensitive workflows.
Shape the Digital Engineering Operating Model: Help define how central platform teams and domain delivery teams collaborate effectively.
Establish lightweight governance through architecture reviews, reusable templates, engineering checklists, design patterns, and production-readiness criteria.
Create onboarding materials, documentation, technical playbooks, starter kits, training paths, reusable examples, and design review practices.
Provide hands-on coaching, office hours, design reviews, and practical guidance to improve developer experience and platform adoption.
Mentor senior engineers and technical leads across Information Sciences and business domains.
Enable Information Sciences and R&D to build digital applications on top of the common platform.
Influence across teams by creating useful standards, practical tools, strong partnerships, and measurable outcomes.