Partner Technical Architect - Agentforce

The Experience

Salesforce is hiring a hands-on Partner Technical Architect to help top SI partners build and ship production-grade Agentforce solutions at scale. In this builder role you will work directly with Partner FDEs to turn ambiguous enterprise AI problems into working solutions, reference implementations, and evaluation harnesses, then use what you learn to raise quality and partner-led outcomes. The best candidate is someone who can build, debug, explain trade-offs, and then package what they learned so many partner teams learn from it. Salesforce and Agentforce experience are valuable, but they are not the whole profile. We are looking first for strong engineering judgment, applied AI fluency, builder instincts, and the ability to ramp quickly into the Salesforce platform.

What You'll Actually Be Doing

• Prototype quickly to validate ideas, expose platform gaps, and unblock first-of-kind implementation risks.
• Build reference implementations, starter kits, demos, field kits, and evaluation harnesses that partners can fork, extend, and deploy.
• Convert field lessons into durable reusable assets: code, diagrams, checklists, decision trees, implementation notes, and architecture guidance.
• Review partner Agentforce architectures for agent design, retrieval strategy, tooling, guardrails, observability, cost, security, and production readiness.
• Coach Partner FDEs and architects through design clinics, office hours, portfolio reviews, and targeted technical walkthroughs.
• Translate recurring field blockers into clear product and engineering feedback.
• Help partners connect technical architecture choices to delivery quality, customer outcomes, and consumption economics.

You're Our Person If...

• You have shipped or seriously prototyped real software, agents, automations, internal tools, or technical demos.
• You can show your work: GitHub repos, demo apps, notebooks, architecture docs, eval harnesses, demo orgs, open-source contributions, or equivalent artifacts.
• You learn new platforms by building with them, not by waiting for perfect documentation.
• You can move fast without losing production instincts around safety, reliability, observability, and maintainability.
• You naturally extract patterns from one-off work and turn them into reusable assets for others.

Applied AI and Agentic Systems

• Experience building with LLMs, agents, RAG, tool use, workflow orchestration, or automation systems.
• Ability to reason about multi-agent, human-in-the-loop, and enterprise integration patterns.
• Comfort debugging agent behavior: traces, logs, failure modes, tool calls, bad context, bad data, latency, and user experience gaps.
• Practical understanding of prompt design, retrieval quality, evaluation, hallucination risk, guardrails, and cost/performance trade-offs.

Enterprise Architecture Judgment

• Ability to communicate clearly with engineers, architects, product teams, partner leaders, and executive stakeholders.
• Strong systems thinking across APIs, data flows, identity, security, integration, observability, and operational handoff.
• Strong product sense: you can distinguish a platform gap, a configuration issue, a partner delivery issue, and a pattern worth codifying.
• Comfort operating in regulated or complex enterprise environments where governance, trust, and delivery risk matter.

Even Better If...

• Hands-on Salesforce, Agentforce, Data Cloud, Apex, Flow, LWC, MuleSoft, or multi-cloud architecture experience is preferred.
• Salesforce certifications are helpful, but not required if you can demonstrate strong builder evidence and rapid platform learning.
• We value candidates who can learn the Salesforce stack quickly and translate broader engineering/AI experience into partner-ready Agentforce patterns.
• Experience working with system integrators, partner delivery teams, or complex enterprise implementation programs.
• Published technical work: open-source projects, internal platform docs, talks, blog posts, or reusable architecture patterns.
• Experience creating maturity models, readiness checks, production-readiness scorecards, or technical review frameworks.
• Familiarity with consumption economics, agent cost modeling, TCO, or outcome-based delivery models.