Principal fullstack engineer - PMTS

Salesforce•Redwood City, CA

1d•$197,300 - $344,700•Hybrid

About The Position

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Are you a seasoned engineer who wants to reshape how the world's largest enterprises harness their data? The Informatica IDMC team—a strategic pillar of Salesforce—is building what comes next: an AI-native data integration platform where Generative AI, LLMs, and Agentic architectures don't just assist workflows—they fundamentally reinvent them. We're talking petabyte-scale data movement that thinks, adapts, and self-optimizes. This is a 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. You won't just design systems—you'll define the patterns that thousands of enterprise customers depend on to run their businesses. We need a high-performing hybrid engineer who leads from the front: shipping production-grade code that powers intelligent data pipelines one day, and elevating an entire team's craft through architectural vision and mentorship the next. If you want to work at the intersection of massive-scale distributed systems and cutting-edge AI—where your decisions directly shape a platform processing more data than most engineers will see in a career—this is the role.

Requirements

Professional Experience: 15+ years of full-time software development in a product or enterprise environment, with a demonstrated track record of technical leadership and delivering high-quality features at scale.
Core Java & Backend Mastery: Expert-level Java with deep understanding of OOP, concurrency, performance tuning, and production-grade code under high load.
Microservices & Spring: Extensive experience with Spring Boot/Spring Cloud—service discovery, event-driven architecture, API gateway patterns, and RESTful API design at enterprise scale.
Cloud Platform Proficiency: Strong experience with AWS, Azure, or GCP—cloud security (IAM, encryption, key management), networking (VPCs, load balancers, service mesh, DNS, WAF), and infrastructure automation.
Containerization & Kubernetes: Production experience with Docker and Kubernetes for orchestration and scaling. Familiarity with Istio, Helm, and deployment tooling (Jenkins, Harness).
Distributed Systems Expertise: Proven experience designing distributed systems—fault tolerance, consistency patterns, and message-driven architectures (Kafka or similar).
Data Persistence: Expert RDBMS knowledge including advanced SQL, query optimization, and transaction management. Experience with NoSQL databases (Cassandra, MongoDB).
Non-Functional Requirements: Deep expertise in designing for availability, scalability, security, and observability. Experience defining SLIs/SLOs and designing rollout strategies.
Technical Leadership: Proven ability to lead one or more teams, set technical direction, mentor engineers, and present to VP-level audiences.
Communication: Excellent written and verbal skills—able to produce architectural documentation, synthesize cross-org guidance, and drive alignment across distributed teams.

Nice To Haves

Distributed Processing: Hands-on experience with Apache Spark, Flink, or similar frameworks.
Data Lakehouse: Experience with open table formats (Iceberg, Delta Lake) or large-scale pipeline patterns.
Data Integration Domain: Experience with ETL/ELT platforms, data quality, or metadata management.
Salesforce/SaaS Ecosystem: Familiarity with Salesforce products or multi-tenant SaaS platform integration.

Responsibilities

AI & LLM Proficiency - Experience with Generative AI, LLMs, and AI-assisted development tools (Claude Code, Cursor). Interest in applying AI to automate data integration workflows.
Technical Leadership & Architecture - Act as the Technical Leader for one or more teams, serving as the go-to technical authority for cross-team plans and problems.
Write architectural documents and design specifications for multi-team projects; negotiate interfaces and resolve cross-team technical issues.
Drive system design for resiliency, reliability, scalability, and efficiency—applying telemetry and observability early in development.
Quality Delivery & Ownership - Embrace full accountability for your team's technical deliveries from code to production, including multiphase rollouts (pre-release, canary, stagger).
Create and approve test strategies with emphasis on non-functional requirements—performance, scalability, security, and fault tolerance.
Define SLIs/SLOs and drive operational excellence for your team's features and services.
Backend Engineering at Scale - Design and build high-performance, fault-tolerant backend services in Java within a cloud-native microservices architecture.
Architect data pipelines and integration workflows that move and transform data across cloud environments at petabyte scale.
Drive platform evolution toward AI-native, Agentic, and Headless patterns.
Agile Execution - Lead Agile processes end-to-end—planning, execution, retrospectives. Own the successful execution of the team's release plan.
Propose medium-term plans (2RR), provide estimates, identify risks, and ensure the team delivers on commitments.
Multiplier Leadership - Coach LMTS engineers and peer teams through design reviews and mentorship. Set clear Definition of Done expectations.
Lead service ownership practices—on-call rotations, readiness reviews, runbooks, and automation that promote team health.
Seek and integrate feedback on your designs; provide constructive feedback on others'.
Communication & Customer Focus - Explain architectures and initiatives clearly to VP-level audiences, Product Owners, and cross-functional partners.
Engage with customers to understand real-world problems; champion Customer Trust in every feature your team builds.
Synthesize external guidance (architecture standards, best practices) and translate it into actionable direction for your teams.