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Software Engineer, AI Systems (PMTS)

Salesforce
San Francisco, USA
Full-time
Onsite
USD 172500-344700 yearly
Discovered 3 weeks ago
LLM-powered systemsPythonGoJavaJavaScript/TypeScriptBackend systems

Full Job Posting

Role overview

Join a 10-person Salesforce AI Labs team bringing computer-use AI into production.

Build Systems Integration Agent, which learns to operate enterprise applications and turns complex workflows into reusable, code-backed automation.

Work directly with customers while shaping architecture across agent and backend systems; own critical capabilities from design through operation.

Agent development and architecture

  • Design systems that learn from demonstrations and combine AI reasoning with deterministic execution.
  • Build recovery and verification so agents adapt to changes, confirm outcomes, and request human intervention when needed.
  • Develop backend services with workflow state management, failure handling, and secure customer-environment access.
  • Create evaluations and diagnostics to measure success, surface regressions, and explain failures.

Customer collaboration and technical direction

  • Prototype and validate customer workflows, investigate automation results, and turn findings into reusable product improvements.
  • Help customers move toward repeatable, self-service adoption; work with forward-deployed engineering and product management on roadmap priorities.
  • Lead architecture across agent execution, backend services, and workflow state; assess models, tools, and context management for reliability, latency, and cost.
  • Contribute through implementation, design reviews, mentoring, and hiring.

Required qualifications

  • Led architecture and delivery of complex backend systems through production deployment and improvement, with impact across components or teams.
  • Hands-on experience shipping and operating LLM-powered systems and using evaluations and production failures to inform design.
  • Can reason about concurrency, persistent state, retries, and partial failures in systems taking consequential actions.
  • Proficient in Python, Go, Java, or JavaScript/TypeScript.
  • Can turn unclear customer problems into bounded technical approaches, test with users, and lead work through production.
  • Interested in direct customer engagement and accountable for the correctness, security, and maintainability of shipped work.

Helpful experience

  • Agent tool use, code generation, automated recovery, or evaluation frameworks are helpful.
  • Browser automation, workflow orchestration, enterprise integrations, early-stage product building, or customer-facing engineering are helpful.

Compensation

  • Typical base salary is $172,500–$313,700 annually; select San Francisco and New York metropolitan areas have a range of $207,800–$344,700 annually.
  • Ranges are base salary only and exclude applicable bonuses, sales incentives, equity, and benefits.

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