AI Builder Partner Solutions

Salesforce • San Francisco, CA

4d • Hybrid

About The Position

This role engages before the buying decision is made, building working solutions against real customer challenges alongside the partners who will deliver them. You are a builder with a voice. You ship working things and explain them in a way that makes other people more confident, more capable, and more willing to bet on the platform. You may come from forward deployed engineering, applied AI engineering, solutions engineering, technical consulting, partner engineering, technical founding, or hands-on Salesforce engineering. You are energized by the loop of seeing a real problem, building the right thing inside an early engagement, explaining it clearly, and then collaborating with partner teams to move it with accelerating quality and confidence.

This is a hands-on builder role. You create technical solution patterns and POCs for live partner and customer environments, always learning what works and what can be made into reusable assets the broader field can extend. The center of gravity is building: agents, on surfaces, using actions/integrations/context, with packaging/evals into deployment patterns. With these elements you provide clear explanations that help field teams trust and reuse the work.

Requirements

• Hands-on experience building on Salesforce platform: Agentforce, Flow, Apex, Lightning Web Components, APIs, permissions, metadata, packaging, and deployment patterns.
• Practical experience building LLM-powered applications: prompt design, context engineering, retrieval and RAG, tool calling and actions, evaluation, and debugging agent behavior.
• Hands-on experience with agentic coding tools as a core part of your daily engineering workflow: Claude Code, Cursor, GitHub Copilot, Windsurf, Codex, or equivalent. You use AI-assisted development to move faster and produce higher-quality output, not as a novelty.
• With Salesforce Headless 360 exposing the entire platform as MCP tools, API endpoints, and CLI commands, the right candidate uses tools like Claude Code or Cursor pointed directly at a live Salesforce org and ships real working implementations faster than anyone building the old way.
• Comfortable building from day 1 in new environments. You can get hands on keyboard inside an unfamiliar partner or customer org and ship working artifacts in your first week.
• Experience integrating enterprise systems through APIs, middleware, MuleSoft, Data Cloud, Slack, or equivalent technologies.
• Comfortable across at least one of Python, TypeScript, JavaScript, Apex, or Java, and comfortable with GitHub-based development workflows.

Nice To Haves

• Experience with Agentforce in real customer or partner implementations.
• Experience with Data Cloud, MuleSoft, Slack platform, Heroku, or Salesforce CLI-based development.
• Experience building or using MCP servers, agent skills, sub-agents, external tools, or multi-agent workflows.
• Experience with GitHub, CI/CD, testing frameworks, evaluation harnesses, packaging, or developer workflow automation.
• Evidence of reusable technical output such as published repos, blog posts, talks, OSS contributions, or community advisory work.
• Experience as a Forward Deployed Engineer, Applied AI Engineer, Solutions Engineer, technical founder, or hands-on AI implementation lead.
• Experience working with GSIs, RSIs, cloud partners, or enterprise implementation partners.
• Familiarity with secure enterprise patterns for authentication, authorization, data access, logging, observability, and governed write actions.

Responsibilities

• Implement working Agentforce/Salesforce solution artifacts for the partner teams to use with the customer during qualification, shaping, and decision phases.
• Build with production-mindset for implementations that handle enterprise requirements such as identity, permissions, governed actions, observability, retrieval quality, and evaluation coverage.
• Create reusable accelerators that travel beyond the engagement: packaged metadata, deployment scripts, install guides, sample data, and test cases.
• Pair directly with partner engineers and customer technical teams to debug, refactor, and harden the implementation in proof-of-concepts & pilots.
• Produce clear walkthrough artifacts that increase Agentforce credibility and reuse: READMEs, partner delivery kits, technical posts, and recorded implementation walkthroughs.
• Present working implementations to experienced engineering audiences and translate fluently between technical and business stakeholders.
• Deliver live technical sessions or co-builds with partner engineering teams that produce reusable artifacts or change their implementation approach.
• Make ambiguous technical problems feel tractable through clarity and hands-on proof.
• Build reusable assets that earn trust before the meeting starts: published implementations, technical posts, GitHub repos, accelerators, and field-ready walkthroughs.
• Help Salesforce earn relevance in AI and data conversations where partner teams already have strong opinions and competing options.
• Represent Salesforce engineering credibility in partner forums, technical sessions, and enablement moments where working proof matters.
• Turn repeatable field patterns into accelerators, solution assets, and Partner FDE Network resources.
• Surface product friction, missing capabilities, and field-proven workarounds back to Agentforce, Data Cloud, MuleSoft, and Slack product and engineering teams.

Benefits

• time off programs
• medical
• dental
• vision
• mental health support
• paid parental leave
• life and disability insurance
• 401(k)
• employee stock purchasing program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed