Principal Fullstack Engineer - Pmts

Salesforce Salesforce · Enterprise · Redwood City, CA

Principal Fullstack Engineer for Salesforce's Informatica IDMC team, focusing on building an AI-native data integration platform. This role involves owning technical direction for teams, making architectural decisions at the intersection of large-scale distributed systems and AI, and shipping production-grade code for intelligent data pipelines. The position requires expertise in Generative AI, LLMs, Agentic architectures, and petabyte-scale data movement, with a strong emphasis on technical leadership and backend engineering at scale.

What you'd actually do

  1. Act as the Technical Leader for one or more teams, serving as the go-to technical authority for cross-team plans and problems.
  2. Design and build high-performance, fault-tolerant backend services in Java within a cloud-native microservices architecture.
  3. Drive platform evolution toward AI-native, Agentic, and Headless patterns.
  4. Create and approve test strategies with emphasis on non-functional requirements—performance, scalability, security, and fault tolerance.
  5. Coach LMTS engineers and peer teams through design reviews and mentorship.

Skills

Required

  • 15+ years of full-time software development
  • Expert-level Java
  • OOP
  • concurrency
  • performance tuning
  • production-grade code under high load
  • Spring Boot/Spring Cloud
  • service discovery
  • event-driven architecture
  • API gateway patterns
  • RESTful API design
  • AWS, Azure, or GCP
  • cloud security (IAM, encryption, key management)
  • networking (VPCs, load balancers, service mesh, DNS, WAF)
  • infrastructure automation
  • Docker
  • Kubernetes
  • Istio
  • Helm
  • deployment tooling (Jenkins, Harness)
  • designing distributed systems
  • fault tolerance
  • consistency patterns
  • message-driven architectures (Kafka or similar)
  • RDBMS
  • advanced SQL
  • query optimization
  • transaction management
  • NoSQL databases (Cassandra, MongoDB)
  • designing for availability
  • scalability
  • security
  • observability

Nice to have

  • Generative AI
  • LLMs
  • AI-assisted development tools (Claude Code, Cursor)
  • applying AI to automate data integration workflows
  • multi-team projects
  • resiliency
  • reliability
  • scalability
  • efficiency
  • telemetry
  • observability
  • full accountability for team's technical deliveries
  • multiphaserollouts (pre-release, canary, stagger)
  • test strategies
  • non-functional requirements
  • performance
  • scalability
  • security
  • fault tolerance
  • SLIs/SLOs
  • operational excellence
  • data pipelines
  • integration workflows
  • cloud environments
  • petabyte scale
  • platform evolution
  • AI-native patterns
  • Agentic patterns
  • Headless patterns
  • Agile processes
  • planning
  • execution
  • retrospectives
  • release plan
  • medium-term plans (2RR)
  • estimates
  • risks
  • team commitments
  • LMTS engineers
  • peer teams
  • design reviews
  • mentorship
  • Definition of Done expectations
  • service ownership practices
  • on-call rotations
  • readiness reviews
  • runbooks
  • automation
  • team health
  • feedback integration
  • constructive feedback
  • VP-level audiences
  • Product Owners
  • cross-functional partners
  • customer trust

What the JD emphasized

  • AI-native data integration platform
  • Agentic architectures
  • petabyte-scale data movement
  • technical leadership
  • shipping production-grade code
  • architectural vision
  • massive-scale distributed systems
  • cutting-edge AI
  • high-performance, fault-tolerant backend services
  • cloud-native microservices architecture
  • AI-native, Agentic, and Headless patterns
  • non-functional requirements

Other signals

  • AI-native data integration platform
  • Generative AI, LLMs, and Agentic architectures
  • petabyte-scale data movement that thinks, adapts, and self-optimizes
  • principal-level engineering role where you'll own the technical direction for one or more teams
  • making architectural bets at the frontier of data integration and AI
  • shipping production-grade code that powers intelligent data pipelines
  • elevating an entire team's craft through architectural vision and mentorship