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Full-Stack/Agentic AI Engineer (Software Engineering MTS)

Salesforce · San Francisco, United States

External listingfull-time21 days ago

About The Role

Join Salesforce's Agentforce engineering team as a Full-Stack/Agentic AI Engineer. You will be responsible for architecting, designing, and shipping scalable full-stack applications on the Agentforce platform. You will work alongside ML engineers, UX experts, and product managers to build intelligent tools for the next generation of AI agents. The role requires a deep knowledge of OOP (Java or Python), experience with multi-agent interaction, and familiarity with Agile/TDD practices.

  • Architect, design, and ship scalable full-stack applications on the Agentforce platform, owning everything from backend API and data modeling to polished, responsive UI experiences.
  • Build and iterate on AI agent tooling using modern agentic frameworks and LLM-backed workflows, contributing to platform-level multi-agent systems and interaction patterns.
  • Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools.
  • Hands-on experience building on agentic platforms (Agentforce, LangChain, AutoGen, CrewAI, or similar) including prompt engineering, RAG patterns, and tool/function calling for generative AI applications
  • A demonstrated, genuine AI-first approach to engineering — using AI tools (e.g., Claude Code, GitHub Copilot, Cursor) to move faster, build fluency across the stack, and contribute well beyond your core specialty
  • A related technical degree required
  • Deep knowledge of OOP (Java or Python) with proven fullstack ability — comfortable owning UI (React/TypeScript), APIs, and backend services within the same product
  • Prior experience with multi-agent interaction, task planning, and LLM orchestration
  • Experience building UI that surfaces AI-generated content — streaming responses, agent traces, and tool call visualization
  • Experience with model evaluation, agent observability, and LLM output quality frameworks
  • Familiarity with Agile/TDD practices and experience supporting production customer escalations

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