Forward Deployed Engineer (All Levels)

Salesforce•Seattle, FL

47d•$88,970 - $198,170•Hybrid

About The Position

Salesforce is hiring Forward Deployed Engineers — experienced Technical Builders who design, build, and deploy agentic AI solutions directly inside enterprise customer environments. You'll work as part of a delivery team, partnering closely with a Deployment Strategist (Strategic Builder - a customer-facing advisor who shapes AI strategy and drives adoption) to co-build solutions that go live in production environments from day one. Engagements range from a single large strategic customer to multiple accounts simultaneously. The common thread is real code, real environments, and measurable business impact. This work spans configuration, customization, and full-stack deployment — shipping solutions customers depend on. The Builder Experience AI-Powered Development: Ship real customer solutions, supported by best-in-class AI tools — Cursor, Claude, and Salesforce coding products like Vibes — embedded into your day-to-day workflow. Collaborative Delivery: You'll work alongside Senior Forward Deployed Engineers and a Deployment Strategist. You'll own real components, benefit from structured mentorship from people who've shipped agentic systems at scale, and have a clear path to leading complex deliveries yourself. Frontier Access: Our agentic AI platform is evolving in real time. You'll work on capabilities most engineers won't touch for months — spanning Agentforce, data, platform, and headless architectures and your field insight will feed directly to the product teams building them. Continuous Innovation: You'll be expected to stay at the forefront, experimenting with emerging AI tools, models, and frameworks, and sharing what you learn with your team and customers.

Requirements

3+ years (6-10 years for Senior levels) of software engineering or technical delivery experience, with at least one production system you'd be proud to walk us through - ideally in an AI tech stack, full-stack development, or working with frontier models
A degree in Computer Science or a related field
Prior customer-facing technical delivery experience (consulting, professional services, or forward deployed engineering) — this is a requirement, not a nice-to-have.
Fluent in at least one of Python, JavaScript/TypeScript, Java, or Apex — and willing to add to that list as the work demands.
Hands-on with LLMs and prompt engineering. You can explain why a prompt failed and what you'd change.
Understand data modeling, APIs, and integration patterns deeply enough to design them, not just consume them.
Can hold your own in a room with sales teams and customer architects.
Ship quality code and evaluate AI outputs with engineering rigor.
Actively tinker with the evolving AI/data landscape — piloting new tools, experimenting with new models, and staying genuinely curious about what's coming next.
Thrive in the group chat that's building something, not just talking about it.
Excited to travel ~25% of the time, working directly alongside customers.

Nice To Haves

Salesforce platform experience or certifications (Administrator, Platform Developer I, Agentforce Specialist)
Familiarity with agent frameworks (LangChain, LlamaIndex) and orchestration patterns
Hands-on with cloud data platforms (Snowflake, Databricks, BigQuery)
Experience across specialist AI delivery areas: data engineering, platform architecture, or headless deployments

Responsibilities

Develop AI agents and experiences that take real actions for real organizations.
Design agent intelligence: prompts, reasoning, tool calls, and integration with customer systems, leveraging our Agentic AI platform and current LLM techniques.
Own technical components end-to-end: from architecture choice to deployed, validated, and observable in production.
Build and integrate data pipelines on Salesforce Data 360, Snowflake, Databricks, and customer data platforms.
Model the data, ship the pipeline, validate the output
Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes.
Contribute to proofs-of-concept and MVPs that move from sketch to deployable in days, not months.
Co-build alongside customers and partners, sharing best practices and enablement as you go.
Leaving teams more capable after each engagement than before.
Surface platform gaps, edge cases, and field insights to senior Engineers and the product team.
Partner with the Deployment Strategist in your pod to translate customer business challenges into agentic solutions that actually ship.