AI Architect - Software Engineering

Salesforce•Palo Alto, CA

4d•Hybrid

About The Position

Salesforce is seeking an AI Cloud Architect to shape the development, deployment, and scaling of agentic systems within the Agentforce platform. This role involves working at the forefront of AI innovation, creating new primitives, incubating next-generation systems, collaborating with customers, and defining the architectural direction for enterprise AI agents in production. It's a hands-on position requiring both coding and communication skills, including writing code, whitepapers, designing runtimes, and presenting to executive leadership.

Requirements

Expertise in distributed systems, stateful runtimes, and LLM-based agent architectures.
Experience building orchestration frameworks, graph-based execution engines, or agent DSLs.
Strong grasp of LLM behavior, context management, and agent reliability in production.
Fluency in Python and Java.
Comfortable with cloud-native infrastructure.
Curiosity about and familiarity with frontier agentic research, including reasoning loops, tool use, memory architectures, and multi-agent systems.
Proven track record of shipping durable technical artifacts such as platforms, frameworks, or open-source projects.
Comfortable transitioning from early-stage experiments to prototypes to General Availability (GA) in fast-moving environments.
Experience with incubation, 0→1 projects, or founding engineer environments is a strong plus.
Exceptional written communication skills, capable of producing design docs and customer whitepapers.
Ability to communicate clearly and credibly with developers, enterprise architects, and CIOs.
Experience engaging enterprise customers as a trusted technical advisor.
Ability to drive alignment across engineering, product, and field teams without requiring direct authority.
A natural teacher and force multiplier who raises the technical bar.

Nice To Haves

Open-source community experience or developer advocacy background.
Familiarity with Salesforce platform primitives (Flow, Apex, Einstein, metadata).
Background in ML infrastructure, data engineering, or AI platform work.
Experience with language/compiler design (relevant to DSL authoring systems like AgentScript).
Familiarity with observability tooling, testing frameworks, or developer experience platforms.

Responsibilities

Invent and incubate fundamental advances in agentic AI, including new execution models, agent orchestration frameworks, and stateful runtime architectures.
Lead incubation projects exploring next-generation agentic systems for the enterprise, such as OpenClaw-style reasoning architectures and multi-agent coordination patterns.
Influence core architectural decisions across Agentforce, focusing on agent determinism, A2A protocols, long-running async workflows, and context engineering.
Contribute to the agent development lifecycle, including Agent Builder, Agent Testing Center, and Agent Observability, to define how developers build, validate, and monitor agents end-to-end.
Partner directly with strategic customers to understand their business context and co-design solutions using Agentforce.
Translate complex agent capabilities into concrete, trustworthy outcomes, from proof-of-concept to production.
Produce technically rigorous and persuasive content, including design docs, engineering blog posts, developer documentation, and external presentations.
Communicate a clear point of view and defend it effectively.