About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. The world of work is changing and Salesforce is looking for Trailblazers passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Agentforce is the future of AI, and you are the future of Salesforce.
The Experience
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, customisation, and full-stack deployment — shipping solutions customers depend on.
Production experience required. Builder mindset non-negotiable.
What You'll Actually Be Doing
•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.
•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. Your real-world experience is the product feedback loop.
•Partner with the Deployment Strategist in your pod to translate customer business challenges into agentic solutions that actually ship.
You're Our Person If...
•Total experience of 8-12 years and with latest 5+ years 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.
•You have a degree in Computer Science or a related field.
•You have prior customer-facing technical delivery experience (consulting, professional services, or forward deployed engineering) — this is a requirement, not a nice-to-have.
•You're fluent in at least one of Python, JavaScript/TypeScript, Java, or Apex — and willing to add to that list as the work demands.
•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 that's building something, not just talking about it.
•You're excited to travel ~25% of the time, working directly alongside customers.
Even Better If...
•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.
