Software Engineer, Mts - Agentforce Optimization Agent & Agent Studio

Salesforce Salesforce · Enterprise · San Francisco, CA

Salesforce is seeking a Software Engineer to join the Agentforce Optimization Agent team, focusing on building an AI-native observability platform for agentic systems. The role involves developing intelligent data pipelines, integrating observability features into Agent Studio and the core Salesforce platform, and optimizing agent reasoning performance. This position requires experience in distributed systems, agentic AI frameworks, and full-stack development.

What you'd actually do

  1. Build intelligent data pipelines: Design and implement scalable systems that query, process, and analyze agent session data from Data Cloud (STDM, Feedback DMOs) with sub-second latency requirements
  2. Ship Agent Studio integrations: Contribute to the Agent Developer Lifecycle (ADLC) by building UI integrations that surface optimization insights directly in the Agent Studio Sessions & Details views — working across the full stack from React frontend to backend services
  3. Optimize agent reasoning performance: Tackle challenging latency problems — output token optimization, reasoning step reduction, tool call chaining — to deliver a responsive user experience while maintaining analytical depth
  4. Build for Salesforce Core at scale: Integrate observability features into the core Salesforce platform, ensuring they work reliably across multi-tenant, multi-cloud production environments with strict security and compliance requirements
  5. Own features end-to-end: From backend services (Java/Python) to data queries to UI components, you'll own features from design through customer deployment

Skills

Required

  • experience building and scaling distributed backend systems or platform services in a production environment
  • strong proficiency in Java, Python, or a comparable language
  • exposure to agentic AI frameworks or LLM-integrated products
  • advanced prompt engineering skills
  • ability to write precise, structured prompts
  • cultivate the system context that makes AI outputs reliable, secure, and production-ready
  • related technical degree

Nice to have

  • experience with intelligent systems, runtime evaluation, automated detection, or observability tooling in large-scale distributed environments
  • worked in a multi-cloud environment (AWS, GCP, or Azure)
  • understand infrastructure-level performance constraints

What the JD emphasized

  • advanced prompt engineering skills
  • production environment
  • strict security and compliance requirements

Other signals

  • building the first AI-native observability platform for agentic systems
  • analyzes millions of agent sessions in production
  • shipping features that directly impact how customers understand and improve their AI agents at scale
  • integrating observability tooling into Agent Studio within Salesforce Core