Senior AI API Platform Engineer

About the Role

The AI API Platform Engineer is a hands-on technical lead who designs and builds the APIs and platform capabilities powering Rubrik's AI-driven products and automation, owning the full API lifecycle across any stack, cloud, or iPaaS. This role delivers secure, scalable, high-performance APIs and full-stack services while enabling AI-native consumption patterns across the enterprise.

Key Responsibilities

• Design and own APIs in any tech stack - REST, GraphQL, gRPC, and webhooks - choosing the right language, cloud service, or iPaaS for each use case.
• Build for AI use cases, exposing data/services as tools for LLMs and AI agents, and enabling RAG and agentic workflows.
• Own core backend engineering in Node.js / Java / Python / Go, with strong data modeling and performance tuning.
• Define API governance - versioning, documentation standards, and reusable auth/error-handling/observability frameworks.
• Provide technical leadership through design reviews, code reviews, and mentoring of engineers.
• Define NFRs and SLAs for availability, latency, throughput, and reliability, and ensure designs meet them.
• Partner with security and compliance to meet regulatory and audit requirements across APIs and integrations.
• Lead technical discovery for new API, integration, and AI-enablement initiatives with product and business stakeholders.
• Drive reuse and standardization through shared APIs, connectors, SDKs, and an integration catalog.
• Evaluate emerging patterns (event-driven integration, AI agent frameworks, low-code automation) to shape the platform roadmap.

Required Qualifications

Experience

• 8+ years of software engineering experience, with 5+ years in API/full-stack/backend development across multiple languages and clouds.
• 2+ years in a senior/lead/architect capacity owning API and platform designs for complex, enterprise-scale systems.
• 1+ years in an FDE role, working directly with internal customers.

Technical Skills - API, Fullstack & Backend

• Deep API expertise across REST, including contract-first design (OpenAPI/Swagger) and robust error handling.
• Strong backend and full-stack skills in Node.js / Java / Python / Go, plus platform-agnostic experience across cloud and iPaaS (MuleSoft, Workato, Boomi).
• Cloud-native development on AWS, Azure, or GCP, including serverless, Kubernetes, and infrastructure as code.
• Strong data skills - SQL and NoSQL database design, plus integration data formats (JSON, XML, CSV).
• Secure API design using OAuth 2.0/OIDC, mTLS, and secrets management, with solid CI/CD and Git-based workflows.
• SaaS integration experience with platforms such as NetSuite, Workday, Salesforce, or Snowflake.
• API Gateway expertise with platforms such as Kong / Apigee / AWS API Gateway / Azure APIM / MuleSoft API Gateway for routing, rate limiting, and policy enforcement.
• API testing proficiency using tools such as Postman for functional and regression testing.
• Networking fundamentals, including VPN/VPC concepts.
• Working knowledge of DevOps practices and toolchains.

Technical Skills - AI & Intelligent Platform Enablement

• Hands-on experience with the AI-assisted SDLC - using AI tools to design, build, test, and manage APIs.
• Experience building APIs for AI consumption, including function/tool-calling interfaces for LLMs and agents.
• Working knowledge of AI/LLM frameworks (OpenAI, Anthropic, LangChain) and vector databases, and how they integrate with enterprise APIs.
• Understanding of AI-specific NFRs - latency, cost, rate limiting, and safety/guardrails.
• Practical experience with AI coding assistants (e.g., GitHub Copilot, Cursor, Claude Code) for AI assisted platform and infrastructure development.

Soft Skills

• Proven ability to lead without authority, driving technical decisions through clarity and data.
• Excellent communication skills, presenting solutions and trade-offs to technical and business stakeholders.

Preferred Qualifications

• Cloud or iPaaS certifications (AWS/Azure/GCP, MuleSoft, Workato, or Boomi).
• Experience in regulated environments (SOX, FedRAMP) with strong auditability and change control.
• Familiarity with event-driven/streaming platforms (Kafka, EventBridge, Event Hubs).
• Hands-on exposure to AI agents, copilots, or LLM-powered features in production.