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.