Software Engineer, AI Systems (PMTS)

About Salesforce

Salesforce is the #1 AI CRM. We are looking for Trailblazers passionate about bettering business and the world through AI and innovation. Agentforce is the future of AI, and this role is the future of Salesforce. Join a team of 10 within Salesforce AI Labs, bringing computer-use AI into production with the autonomy of a small startup and the reach of Salesforce. We are building the Systems Integration Agent, which learns how to operate enterprise applications and turns complex workflows into reusable, code-backed automation.

About the Role

As a Principal Engineer, you will remain hands-on while shaping architecture across our agent and backend systems, owning critical capabilities from design through operation, and helping other engineers deliver them. You'll help answer hard engineering questions about how AI agents know they succeeded, when to reason vs. follow deterministic paths, and how to recover from application changes or ask for help. Our team works directly with customers, building alongside them and turning discoveries into reusable product capabilities.

Key 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 & Tech Stack

• 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.

Helpful Experience

• Agent tool use, code generation, automated recovery, or evaluation frameworks.
• Browser automation, workflow orchestration, or enterprise integrations.
• Building an early-stage product or working in a customer-facing engineering role.