Forward Deployed Engineer (FDE) (Mid/Senior Level)

We are Salesforce, the Customer Company, inspiring the future of business with AI + Data + CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer too, driving your performance and career growth, charting new paths, and improving the state of the world.

If you believe in business as the greatest platform for change and in companies doing well and doing good, you've come to the right place.

About the Role

Builder mindset non-negotiable.

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 versatile delivery team.

Depending on the engagement, you may partner closely with a Deployment Strategist (Strategic Builder — a customer-facing advisor who shapes AI strategy and drives adoption) or work in an AI-augmented delivery model alongside agents and other specialists. You should be comfortable adapting how you work while maintaining clear ownership of customer outcomes.

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, customisation, and end-to-end 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.
• Hands-On Delivery: You’ll be hands-on keyboard from day one, owning and building real components that ship as part of customer engagements. You’ll work alongside Senior Forward Deployed Engineers and, depending on the engagement, Deployment Strategists, AI agents, and other specialists to solve complex problems and deliver production-ready solutions. Along the way, you’ll have access to structured mentorship from people who’ve shipped agentic systems at scale, while building toward owning and leading increasingly 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.

What You'll Actually Be Building

• Develop AI agents and experiences that take real actions for real organisations. Our solutions are in production at some of the largest enterprises on the planet. The work matters because the customers depend on it.
• Build 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.
• Product Feedback Loop: Serve as a direct feedback loop between the field and product — surfacing platform gaps, edge cases, and real-world insights to senior Engineers and Product teams. What you learn while building and deploying directly informs how the product evolves.
• Partner with the Deployment Strategist, AI agents, and other members of your pod as the engagement requires to translate customer business challenges into agentic solutions — building, testing, iterating, and delivering solutions that actually ship.

You're Our Forward Deployed Engineer If…

• You bring relevant software engineering or technical delivery experience — ideally in an AI technology stack, end-to-end solution development, or working with frontier models — or formal education in computer science, information technology, engineering, or a related field. Placement within grades 5–10 will be determined by the depth and years of relevant experience.
• You have prior hands-on technical experience in engineering, support engineering, consulting, solution engineering, professional services, or forward deployed engineering — with experience solving complex technical problems and delivering solutions in customer-facing or internal environments.
• You've been hands-on with LLMs and prompt engineering. You can explain why a prompt failed and what you'd change.
• You understand data modeling, APIs, and integration patterns deeply enough to design them, not just consume them.
• You can hold your own in a room with sales teams and customer architects.
• You ship quality code and evaluate AI outputs with engineering rigor.
• You actively tinker with the evolving AI/data landscape — piloting new tools, experimenting with new models, and staying genuinely curious about what's coming next.
• You thrive in the group chat where everyone is contributing, building, and moving the work forward — not just talking about it.
• You're 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) are valued but not required. Candidates without prior Salesforce experience may be considered for roles up to grade 6, based on demonstrated technical depth and delivery experience.
• 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