Software Engineering SMTS - Brain Team (REMOTE)
$149k - $224k • Remote • California - San Francisco
Posted 6d ago
Job Location
California - San Francisco
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Agent Engineer
About the job
Salesforce is seeking a Software Engineering SMTS for the Brain Team, focusing on the intelligence layer behind their AI CRM product, Piper. This role involves building, maintaining, and upgrading AI agents that qualify leads and book meetings. You will work on system prompts, model configuration, context layers, evaluations, and the underlying harness that powers Piper. The position offers a high-ownership, high-velocity environment where engineers ship customer-facing AI products at scale, with end-to-end ownership from idea to production. You will collaborate with product and AI platform teams to develop features, enhance customer experiences, and build evaluation systems to ensure agent performance and business outcomes.
Responsibilities
- Build and maintain AI agents for lead qualification and meeting booking.
- Develop and manage system prompts, model configurations, and context layers for AI agents.
- Create and maintain LLM evaluations to measure agent health and response quality.
- Collaborate with product teams to integrate AI agent experiences into customer platforms.
- Ensure AI agent changes contribute to business outcomes like lead conversion and pipeline generation.
- Troubleshoot LLM responses and identify issues within agent traces.
- Contribute to the development of agent evaluation systems.
- Automate tasks and build domain expertise using coding agents.
Requirements
- Minimum of 5 years of experience in product engineering or related fields.
- Customer-centric thinking and ability to translate customer needs into agent tuning.
- Strong full-stack fundamentals in frontend and backend development.
- Ability to work independently, engage with product experts, and own ideas through production.
- Understanding of core agent building blocks: traces, context, tokens, tools, system prompts, models, latency, reasoning tradeoffs, and MCP.
- Familiarity with troubleshooting LLM responses and identifying issue sources.
- Experience with an LLM observability system is a plus.
- Experience building software for marketing, sales, or go-to-market teams, especially with Salesforce and CRM integrations.
- Understanding of customer data, lead qualification, routing, and sales workflows.
Benefits
- Foundational impact on AI agent capabilities and tooling.
- Opportunity to lead significant projects end-to-end with growing scope and influence.
- Own the platform as it scales, from retrieval to model providers to agent orchestration.
- Set performance and reliability standards for AI products.
- Turn new AI capabilities into dependable customer experiences.
- Strong engineering practices around evaluation, observability, and iteration.
- High bar for engineering craft and decisive execution.
- Room for technical and product scope growth, including leading projects and influencing architecture.