Description
Join Salesforce AI Labs, a team of 10, in building Systems Integration Agent, which learns how to operate enterprise applications and turns complex workflows into reusable, code-backed automation.
As a Principal Engineer, you will design and build systems that learn from demonstrations and combine AI reasoning with deterministic execution to complete workflows reliably.
Responsibilities:
- Drive Agent Development & Architecture
- Design and build systems that learn from demonstrations and combine AI reasoning with deterministic execution to complete workflows reliably.
- Develop recovery and verification capabilities so agents can adapt to changes, confirm outcomes, and recognize when human intervention is needed.
- Build backend services with robust workflow state management, failure handling, and secure access to customer environments.
- Create evaluations and diagnostics that measure task success, expose regressions, and make failures understandable.
- Build Directly With Customers
- Work alongside customers to understand their workflows, prototype solutions, and validate results in their environments.
- Investigate where automation succeeds or fails, then turn those findings into improvements to the core product.
- Help customers move from their first successful workflow toward repeatable, increasingly self-service adoption.
- Partner with forward-deployed engineers and product management to decide which customer needs should shape the roadmap.
- Shape Technical Direction & Grow the Team
- Lead architectural decisions across agent execution, backend services, and workflow state, aligning system boundaries and tradeoffs with other technical leads.
- Evaluate model selection, tool use, and context management against reliability, latency, and cost.
- Raise the engineering bar through hands-on implementation, design reviews, and mentoring; help engineers take on broader ownership and participate in hiring.
Requirements:
- You've led the architecture and delivery of complex backend systems through deployment, production failures, and subsequent improvements, with impact across multiple components or teams.
- You have hands-on experience shipping and operating LLM-powered systems, and can explain how evaluations and production failures informed your design decisions.
- You can reason through concurrency, persistent state, retries, and partial failures in systems that perform consequential actions.
- You're proficient in Python, Go, Java, or JavaScript/TypeScript.
- You can turn an unclear customer problem into a bounded technical approach, test it with users, and lead it through production while creating capabilities other engineers can build on.
- You want direct customer engagement to be part of your engineering work, including investigating problems and discussing technical tradeoffs.
- You use AI development tools thoughtfully and take responsibility for the correctness, security, and maintainability of what you ship.
The typical base salary range for this position is $172,500 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $344,700 annually.