Software Engineering LMTS- AI/LLM

About the role

Trust is Salesforce’s #1 value.

Within the Salesforce Trust Platform (STP), the Trust Intelligence Platform (TIP) engineering organization builds the 360° security‑intelligence layer protecting every Salesforce asset across our public‑cloud substrates and private infrastructure.

Inside TIP, the Trusted Supply Chain (TSC) team owns the services that secure the design, code, build, and run phases of the Salesforce SDLC – used by thousands of internal developers shipping the world’s largest Saa S platform.

As Lead MTS in TSC, you will own the architecture and engineering roadmap for our trusted‑supply‑chain platform: third‑party‑package security, vulnerability management, attribution, remediation, and runtime defense.

You will be the authoritative voice on technical tradeoffs, the most active evangelist for next‑generation security engineering, and the mentor who raises the technical bar for the engineers around you.

This is a builder’s role for a senior IC who wants to define what supply‑chain security looks like in the agentic‑AI era – not just instrument the SDLC, but redesign it.

What you will do

• Own the architecture vision and multi‑year roadmap for Salesforce’s Trusted Supply Chain platform – scanning, attribution, remediation, and runtime defense across public cloud and private infrastructure.
• Lead the AI‑native rebuild of our supply‑chain stack.

Design and ship agentic systems that triage findings, author fixes, validate them in CI, and close the loop without human keystrokes for the well‑understood cases – freeing engineers to focus on novel risk.

• Champion operational excellence. Feed incident learnings back into design. Build for fault isolation, graceful degradation, and observability from day one.
• Partner with PMs and EMs on build‑vs‑buy decisions and time‑to‑market vs. long‑term sustainability tradeoffs.
• Coach Salesforce application teams on supply‑chain and App Sec best practices; be the voice of TSC in the Salesforce Principal community.
• Track and adopt the most relevant trends in supply‑chain security, agentic App Sec, ML‑assisted vulnerability discovery, secure software development, and AI safety.
• Mentor engineers – advocate for their contributions and career development; raise the technical bar across the team.
• Required skills and experience
• M. S. or Ph. D. in Computer Science or equivalent practical experience.
• 10+ years building applications or systems software at scale.
• 5+ years in public‑cloud environments with container‑based technologies (Docker, Kubernetes, Istio, service mesh).
• Strong, active coding skills in at least two of Go, Java, Python, Rust, C# , with deep attention to code quality and secure‑by‑default patterns.
• Experience with stateful, service‑oriented architectures and the design tradeoffs they impose (consistency, partitioning, recovery).
• Experience with relational and No SQL stores and pub/sub messaging (Kafka, Rabbit MQ, SQS).
• Demonstrated ability to define technology strategy and execute multi‑year roadmaps through ambiguity.
• Track record of incremental architectural evolution, refactoring, and safely prototyping new features in production.
• Excellent written and verbal communication; proven ability to drive alignment with executives, peers, and engineers on contentious technical decisions.
• AI / agentic engineering
• Hands‑on experience building production systems with LLMs – RAG pipelines, function/tool calling, structured output, evals, guardrails.
• Working knowledge of agentic patterns: multi‑agent orchestration, planner/executor loops, tool‑augmented reasoning, agent memory and context management, human‑in‑the‑loop checkpoints.
• Practical fluency with the modern AI developer stack – at least one of Anthropic Claude, Open AI or similar foundation‑model APIs; agent frameworks (Lang Graph, Crew AI, Auto Gen, or equivalent); MCP (Model Context Protocol); evaluation harnesses (Lang Smith, Braintrust, custom).
• Proven daily use of AI‑assisted coding tools (Claude Code, Cursor, Copilot) including authoring custom agents, slash commands, hooks, and skills – and a clear point of view on when to use them and when not to.
• A realistic posture on AI safety and reliability: prompt‑injection defense, sandboxing untrusted tool calls, deterministic test harnesses, regression evals, cost/latency budgeting, and graceful degradation when the model gets it wrong.
• Equal Employment Opportunity

Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment.

We believe in equality for all and strive to create a workplace that is inclusive and free from discrimination.

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 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.

#J-18808-Ljbffr