Product Deployed Engineer

Salesforce•San Francisco, CA

7d•$197,300 - $344,700•Hybrid

About The Position

The Customer Engineering team is Salesforce's zero-to-one product hardening function for Service Cloud and Agentforce. We embed senior engineers directly with a small portfolio of selected lighthouse customers — getting Agentforce Service capabilities live in production, fast, and fixing what we find at the product level. Every engagement produces two outputs: a working customer deployment and product improvements. Blockers are resolved in the codebase, not in bespoke workarounds. Field learnings feed directly into the Agentforce product roadmap. We sit where engineering sits. We are hiring a Product Deployed Engineer to embed with lighthouse customers across the full Agentforce Service Cloud portfolio — Help Agent, Voice, NGA/Script, Service Rep Assistant, and Self Service. You will own end-to-end delivery within your customer pod: from initial deployment through production hardening. You will resolve the blockers others cannot, ship fixes into the core product, and turn every field learning into a reusable asset the broader Salesforce ecosystem can deploy at scale. This is not configuration work. This is senior product engineering with a live customer on the other side of every decision.

Requirements

8+ years of software engineering or technical delivery experience, with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS.
Expert in at least one of Python, JavaScript/TypeScript, Java, or Apex — and conversant in the others. Full-stack/polyglots who can solve problems regardless of the specific technical stack.
Hands-on production experience with AI technologies, machine learning, NLP, and LLMs (prompt engineering, grounding, RAG, agent orchestration). You can diagnose why a solution is failing and ship the fix for both the customer and the core platform.
Extensive, deep understanding of the Salesforce platform and ecosystem (Agentforce, Apex, LWC, Flows, APIs). You know the platform well enough to find its edges.
Exceptional analytical skills with a passion for customer success. You have a strong desire to help customers achieve their goals through AI innovation, thriving in ambiguity and adapting quickly to new challenges.
Proactive, self-starter with an entrepreneurial, "get-things-done" mindset. You drive fast delivery and possess strong ownership, but you also have the judgment to know when fast is the wrong call.
Track record of working effectively in cross-functional teams to create reusable assets—frameworks, playbooks, and internal tooling that others build from.
Excellent written and verbal communication skills. You communicate clearly and credibly, with the ability to explain complex technical concepts to engineering peers, customer architects, executive stakeholders, and non-technical audiences.
Thrives in a fast-paced, dynamic environment and is comfortable with change. Excited to travel ~25% of the time, building strong relationships while embedded with customer engineering teams on-site.

Nice To Haves

Salesforce certifications: Platform Developer I/II, Agentforce Specialist, System Architect, Data Cloud.
Deep experience in data modeling, processing, and AI readiness — across Salesforce Data Cloud, Snowflake, Databricks, or equivalent platforms.
Experience with agent frameworks: LangChain, LlamaIndex, or equivalent orchestration patterns.
Familiarity with DevOps/CI-CD practices, observability tooling, and data governance in enterprise environments.
Prior customer-facing technical delivery: consulting, FDE, or professional services.
Open-source contributions, published technical writing, or conference presentations.

Responsibilities

Embed with selected lighthouse customers across Agentforce Service use cases — Help Agent, Voice, NGA/Script, Service Rep Assistant, Agentic Self Service — and get them live in production.
Own technical delivery end-to-end: architecture decisions, agent logic, integration design, deployment, and production validation.
Resolve customer blockers at the product level — shipping fixes into the Agentforce codebase, not into one-off customer workarounds. 80%+ of blockers resolved via product code (the two-check-in model).
Design and build agentic systems on the Agentforce platform: agent topics and actions, tool calls, multi-agent orchestration, MCP and the integration patterns that hold up in enterprise environments.
Own the data lifecycle for each deployment: knowledge readiness, data modeling, pipeline design, and AI readiness.
Contribute field learnings, reusable skills, and observability patterns to the Agentforce product team — your work becomes the standard others deploy from.
Surface platform gaps and edge cases directly to Product & Engineering. Your real-world production experience is the most credible input to the Agentforce roadmap.
Mentor engineers within your pod through code reviews, paired sessions, and shared delivery. Your engineering standards propagate.
Operate at 3x engineering productivity — 100% AI-tooled with Cursor, Claude, and Salesforce coding products embedded into every delivery.