Forward Deployed Engineer (All Levels)
Role details
Job location
Tech stack
Job description
- 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.
What You'll Actually Be Building
- Develop AI agents and experiences that take real actions for real organizations. 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.
Requirements
Production experience required. Builder mindset non-negotiable., * You have 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
- 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.
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
Benefits & conditions
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is, $88,970 -