Description

Department: Software Engineering – Informatica CDGC Unit

About Us

At Salesforce, we are the global leader in CRM, bringing companies and customers together in the digital age. We are a team of Trailblazers building the future, and Trust is our number one value.

Welcome to the era of the Agentic Enterprise. We are rapidly expanding our Informatica Cloud Data Governance and Catalog (CDGC) unit to meet the massive, unprecedented challenges of the AI revolution. This team is at the bleeding edge of enterprise data intelligence, and we are looking for a visionary Principal Member of Technical Staff (PMTS) to join our Core Metadata Platform team.

This team powers the deeply complex, highly scalable backend that serves as the brain of CDGC. If you are a battle-tested engineering rockstar who thrives on solving the hardest, most ambiguous challenges in the AI world and wants to define the foundational architecture for the Agentic Enterprise, you belong here in our Ohana.

The Role

As a PMTS on the Core Metadata Platform, your mission is to bridge the gap between traditional distributed systems and the wild frontier of autonomous AI. You will be responsible for architecting solutions that solve profound business and technical challenges for the Agentic Enterprise.

How do we securely expose massive-scale enterprise metadata to autonomous agents? How do we ensure deterministic governance over probabilistic AI models? How do we build a dynamic, intelligent graph that agents can reason over with zero latency and absolute trust?

These are the challenges you will solve. You will define the architectural north star, building agentic-ready capabilities directly into the CDGC backend, and empowering our enterprise customers to unleash AI on their data safely and effectively.

Your Impact

Pioneer the Agentic Enterprise: Architect and implement the foundational backend systems that allow autonomous AI agents to seamlessly and securely interact with enterprise metadata, execute complex workflows, and make data-driven decisions.

Solve Hard AI Challenges: Tackle the toughest problems in enterprise AI, including scaling RAG (Retrieval-Augmented Generation) pipelines, building robust semantic search capabilities, mitigating LLM hallucinations through strictly governed metadata ground-truth, and designing fail-safe guardrails for agentic actions.

Architect for Extreme Scale: Design highly resilient, distributed backend architectures that can handle the extreme computational and data retrieval loads generated by concurrent AI agent activity.

Drive Technical Innovation: Stay ahead of the rapidly evolving AI landscape (e.g., advanced reasoning frameworks, multi-agent orchestration, LangChain, LlamaIndex). Drive high-stakes proofs-of-concept into enterprise-grade production reality.

Cross-Functional Leadership: Partner directly with Product Management, AI Researchers, and Data Science to translate ambiguous enterprise AI needs into elegant, high-performing technical solutions.

Elevate the Engineering Bar: Act as a force multiplier. Mentor senior architects and engineers, lead massive cross-functional technical initiatives, and set the standard for code quality and system design across the CDGC unit.

What We Are Looking For (Must Haves)

Experience: 15+ years of hands-on software engineering experience with a proven track record of architecting, building, and scaling deeply complex, high-throughput distributed backend systems.

AI & Agentic Readiness: Deep readiness and proven ability to solve novel challenges in the AI world. Strong working knowledge of LLM integration, agentic frameworks, semantic reasoning, vector embeddings, and RAG architectures.

Distributed Compute: Deep expertise in building, optimizing, and operating distributed computing architectures and large-scale data processing engines (hands-on experience with Apache Spark is highly preferred).

Platform Architecture: Deep mastery of metadata management, highly scalable graph databases, distributed caching, and microservices architecture.

Security & Trust: Experience building systems where security, data governance, and access control are paramount—specifically designing these guardrails for machine-to-machine or agent-to-system interactions.

Cloud Native: Extensive experience building on public cloud infrastructure (AWS, GCP, or Azure) using Kubernetes, Docker, and serverless technologies.

Leadership: Demonstrated ability to lead complex, multi-year technical initiatives from inception to delivery, commanding the respect of both elite engineering teams and executive stakeholders.

Language Mastery: Expert-level proficiency in backend programming languages such as Java, Go, or C++.

Education: BS/MS/PhD in Computer Science, Engineering, or a related technical field.

Preferred Qualifications (Nice to Haves)

Modern Data Lake Architectures: Experience with modern open table formats such as Apache Iceberg is preferred

Deep domain expertise in Data Governance, Data Catalogs, or enterprise Master Data Management (MDM).

Experience with massive-scale graph databases (e.g., Neo4j, Neptune) and complex query languages (Gremlin, Cypher).

Active contributions to cutting-edge open-source projects in the data, AI, or distributed systems space.

A strong builder mentality with a passion for navigating the ambiguity of the AI space and delivering rapid, iterative value to customers.