Manager Salesforce Database Jobs in California (NOW HIRING)

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

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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.

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.

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.

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Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education. In the United States, compensation offered will be determined by factors such as location, job level, job‑related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at https://www.salesforcebenefits.com. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $97,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

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