Partner Technical Architect - Agentforce

Salesforce Salesforce · Enterprise · Dublin, Ireland

Salesforce is seeking a Partner Technical Architect to help SI partners build and scale production-grade Agentforce solutions. This role involves prototyping, building reference implementations, reviewing partner architectures, coaching partners, and providing feedback to product and engineering teams. The ideal candidate has strong engineering judgment, applied AI fluency, builder instincts, and experience with LLMs, agents, RAG, and enterprise architecture.

What you'd actually do

  1. Prototype quickly to validate ideas, expose platform gaps, and unblock first-of-kind implementation risks.
  2. Build reference implementations, starter kits, demos, field kits, and evaluation harnesses that partners can fork, extend, and deploy.
  3. Convert field lessons into durable reusable assets: code, diagrams, checklists, decision trees, implementation notes, and architecture guidance.
  4. Review partner Agentforce architectures for agent design, retrieval strategy, tooling, guardrails, observability, cost, security, and production readiness.
  5. Coach Partner FDEs and architects through design clinics, office hours, portfolio reviews, and targeted technical walkthroughs.

Skills

Required

  • 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.
  • 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.

Nice to have

  • 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.

What the JD emphasized

  • production-grade Agentforce solutions at scale
  • build, debug, explain trade-offs
  • applied AI fluency
  • agent design
  • retrieval strategy
  • tooling
  • guardrails
  • observability
  • production readiness
  • regulated or complex enterprise environments

Other signals

  • building production-grade Agentforce solutions at scale
  • turn ambiguous enterprise AI problems into working solutions
  • raise quality and partner-led outcomes
  • build, debug, explain trade-offs, and then package what they learned