Senior Integration & Automation Engineer

Rubrik Rubrik · Enterprise · Bangalore, India · Information Technology & Services

Senior Integration & Automation Engineer responsible for designing, building, and governing secure, scalable APIs and integrations between enterprise platforms and third-party systems. The role will embed AI capabilities (LLMs, decisioning services, intelligent workflows) into APIs and business processes, defining API-first, AI-aware integration patterns and standards. Leverages MuleSoft Anypoint Platform (or similar iPaaS) and works closely with stakeholders to ensure security, reliability, and observability.

What you'd actually do

  1. Own the API and integration architecture and strategy for assigned domains, defining API-led patterns (Experience, Process, and System APIs), reference architectures, and standards for how systems integrate across the enterprise.
  2. Design, build, and evolve RESTful APIs that expose well-designed resources and operations to internal and external consumers, with clear contracts, documentation, and SLAs.
  3. Lead implementation of integrations between SaaS and on-prem applications (e.g., NetSuite, Workday, Salesforce, Snowflake, ServiceNow), Finance, HR, Security, and GTM platforms, ensuring solutions are scalable, secure, resilient, and observable.
  4. Create data integration strategies for high volumes of data in transit, optimizing for performance, reliability, and cost (e.g., streaming vs. batch, push vs. pull APIs, caching, backoff strategies).
  5. Define and enforce API governance, including:

Skills

Required

  • API architecture and strategy
  • RESTful API design and development
  • Enterprise integration patterns
  • MuleSoft Anypoint Platform (or similar iPaaS)
  • Data integration strategies (streaming vs. batch)
  • API governance
  • Technical leadership
  • Solutioning and design reviews
  • Code reviews
  • REST/SOAP APIs, webhooks, messaging interfaces
  • API gateway management
  • Non-functional requirements (NFRs) and SLAs definition
  • Observability and reliability for APIs and integrations
  • Logging, tracing, metrics, dashboards, and alerting
  • Operational runbooks
  • AI opportunities identification and prioritization
  • AI usage definition and governance
  • Integration with AI platforms and services (model APIs, vector stores, feature stores)
  • API design and security practices
  • Security, privacy, and regulatory requirements
  • Technical discovery and solution design
  • Vendor and platform technical relationships
  • CI/CD practices for APIs, integrations, and AI services
  • Automated testing (unit, integration, regression)
  • Shared asset development
  • KTLO/on-call rotations
  • Incident response and post-incident reviews
  • Communication with technical and non-technical audiences
  • Architecture diagrams, decision records, and documentation
  • 10+ years of overall software/integration engineering experience
  • 8+ years focused on API and enterprise integrations
  • 4+ years in a senior/lead/architect capacity

Nice to have

  • LLMs
  • Claude
  • decisioning services
  • intelligent workflows
  • NetSuite
  • Workday
  • Salesforce
  • Snowflake
  • ServiceNow
  • JSON
  • XML
  • CSV
  • SOX-sensitive data flows

What the JD emphasized

  • AI-driven automation strategy
  • embed AI capabilities
  • API-first, AI-aware integration patterns and standards
  • MuleSoft Anypoint Platform
  • AI opportunities within API and integration flows
  • safe and governed AI usage
  • Integrate with AI platforms and services
  • Partner with security, compliance, and audit teams
  • regulatory requirements
  • AI-automation initiatives
  • AI services
  • AI services
  • AI solutions

Other signals

  • embedding AI capabilities into APIs and business processes
  • designing, building, and governing secure, scalable APIs and integrations
  • API-first, AI-aware integration patterns and standards
  • integrating with AI platforms and services (internal or external), including model APIs, vector stores, and feature stores