> Markdown version of [/jobs/ext/2697112-principal-software-engineer-data-scientist-ai](https://www.wearedevelopers.com/jobs/ext/2697112-principal-software-engineer-data-scientist-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Software Engineer / Data Scientist, AI - **Company:** Salesforce Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $97,300.0 - $313,700.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Software as a Service, Databases, Data Deduplication, Database Schema, Distributed Data Store, Distributed Systems, Graph Database, Python (Programming Language), Operational Databases, Salesforce.Com, Workflow Management Systems, Cloud Platform System, Large Language Models, Machine Learning Operations - **Published:** September 3, 2026 - **Apply:** https://salesforce.wd12.myworkdayjobs.com/External_Career_Site/job/California---San-Francisco/Principal-Software-Engineer---Data-Scientist--AI_JR357716 ## About the Role * Hands-on experience building and shipping full-stack, full-lifecycle agentic AI systems in production - LLM orchestration, tool and MCP integration, retrieval and knowledge grounding, and evaluation.. * Strong programming in Python and Java in a Unix/Linux environment; solid grasp of distributed systems.. * Judgment about what makes agents reliable at scale: grounding, evaluation, and guardrails against the failure modes - hallucination, context drift, wrong remediation - that cause incidents.. * Familiarity with the modern data and agent stack a plus: tracing and experiment tracking (e.g. MLflow), workflow orchestration (e.g. Airflow), distributed query engines (e.g. Trino), knowledge graphs, and model-agnostic gateways across frontier models.. * Track record of shipping and operating production software at scale, with a bias for hands-on delivery over specification.. * Experience building automation for root-cause analysis and self-remediation of production systems is a strong plus.. * Strong written and verbal communication; able to drive AI discussions across engineering teams and influence without authority.. * Background and experience in Data Science highly desirable. You should have 10+ years of professional experience. Experience with large-scale distributed databases or multi-tenant SaaS architectures is a strong plus. ## Description The SDB AI team builds the foundation that makes agentic engineering on Salesforce Database safe, correct, and reusable across the org. Salesforce Database is the multi-tenant production database behind Salesforce's cloud platform no general-purpose model knows. We encode that database-specific knowledge, prove that agents acting on it behave correctly, and take agentic work all the way to production. What You'll Do You will own the design and hands-on implementation of the agentic AI foundation for database engineering and operations: full-stack, full-life-cycle agentic engineering and workflow automation, knowledge graphs and agentic memory, and unified agentic evaluation with data curation. Your work will span: * Build the agentic memory the agents reason over - the knowledge and context graphs that hold the database schema, runbooks, query templates and escalation-policy - and keep it accurate as the database evolves.. * Build closed-loop evaluation as infrastructure: local tracing, replay and golden-trace regression, PR-gating, and scoring against domain-grounded rubrics - proving not only that output is correct but that the execution path is.. * Advance the production agent from workflow-shaped to agent-shaped: a dynamic, causal planner and the specialized tools database workflows need beyond off-the-shelf MCP.. * Take agentic work all the way to production - through the platform, identity, and integration layers where the real bottleneck lives - and operate it at machine speed across hundreds of incidents a week with high-accuracy root-cause analysis, capacity planning, and early detection of anomalous events - with high-accuracy outcomes.. * Build the guardrails and telemetry that keep agents grounded: context-drift detection, activation instrumentation, and failure-mode analysis.. * Partner with database engineering teams to turn one team's pattern into every team's starting point - paved paths, deduplication, and quality gating that convert org-scale sprawl into one trustworthy library.. ## Related Videos - [The AI-Native Engineering Org: What’s Real, What’s Hype, What’s Next](https://www.wearedevelopers.com/videos/100004-the-ai-native-engineering-org-what-s-real-what-s-hype-what-s-next) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Graphs and RAGs Everywhere... But What Are They? - Andreas Kollegger - Neo4j](https://www.wearedevelopers.com/videos/1311-graphs-and-rags-everywhere-but-what-are-they-andreas-kollegger-neo4j) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)