Senior Forward Deployed Engineer

• Salesforce is hiring Senior Forward Deployed Engineers — the Technical Builders, responsible for deciding that leads who design, build, and deploy the most complex agentic AI solutions directly inside enterprise customer environments
• You’ll lead technical delivery on your team, mentor the next wave of engineers, and set the engineering standards that define how agentic AI gets deployed at scale
• Partnering closely with a Deployment Strategist (Strategic Builder - a customer-facing advisor who shapes AI strategy and drives adoption), you’ll own outcomes end-to-end, from architecture decision to production
• Your passion for well-crafted software that solves real problems will be supported by best-in-class AI tools and a team of talented builders around you
• Technical Ownership: Partner with a Deployment Strategist to own customer outcomes end-to-end
• You’re the senior technical authority in the room, ensuring deliverables meet the highest engineering standards, whether it was generated by an AI tool by a colleague or written by you directly
• AI-Supported Engineering: Cursor, Claude, and Salesforce coding products like Vibes are embedded in your daily workflow
• The conventions and patterns you develop tend to propagate through the team because other Builders look to your work as reference
• Roadmap Influence: Your field experience routes directly to Product and Engineering
• The gaps you hit and the edge cases you encounter in real life customer environments become the features they ship
• Senior Forward Deployed Engineers are the most credible voice in agentic AIproduct evolution
• Continuous Innovation: You’re expected to stay at the forefront — piloting emerging AI tools, experimenting with new models and frameworks, and sharing what you learn with your team and customers
• Own end-to-end build and deployment of agentic AI solutions for Salesforce’s most strategic customers — from architecture decisions through production handoff
• Design and ship agentic systems on the Agentforce platform: agent logic, tool calls, multi-agent orchestration, deterministic guardrails, and the integration patterns that hold up in enterprise environments
• Your reference implementations become the basis for how other Builders approach similar problems
• Own the data lifecycle: model design, processing pipelines, and data readiness for AI applications across Salesforce Data 360, Snowflake, Databricks, and customer-specific platforms
• Resolve the technical blockers that other engineers can’t — data integration failures, model deployment issues, orchestration breakdowns, performance regressions
• These problems are routed to you because of your track record of solving them
• Build and maintain agent performance dashboards and customer KPI reporting to track deployment health and business outcomes across engagements
• Develop proofs-of-concept and MVPs quickly, with the judgment to know which decisions can be deferred and which need to be right the first time
• Codify what you learn
• The patterns, reusable assets, and internal frameworks that come out of your real customer work become the playbooks the rest of the org draws from
• Mentor other Engineers through code reviews, pair sessions, and shared work
• Most of your influence on developing engineers happens inside the same codebases you’re building in
• Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed
• Surface field insights directly to Product and Engineering
• The gaps and edge cases you encounter in real customer environments are some of the most valuable inputs to the Agentforce roadmap
• Partner with the Deployment Strategist on your team to translate complex customer business challenges into agentic solutions that actually ship

Benefits

• Medical Care
• Life Insurance
• Retirement Savings
• Employee Assistance Programs
• With 9 standard holidays and four floating holidays, you get a total 13 paid days off each year- Technical depth required
• Architectural judgment expected
• You bring deep Salesforce platform expertise: Agentforce, Apex, LWC, Flows, and Salesforce APIs
• You’re an expert in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in the others
• You’re excited to travel ~25% of the time, embedded with customer engineers
• You have an entrepreneurial, get-things-done mindset focused on fast, impactful delivery — and the judgment to know when “fast” is the wrong call
• You’ve integrated LLMs into production, used frameworks like LangChain or LlamaIndex, and applied prompt engineering and responsible AI practices in real customer contexts
• You have 6+ years of software engineering or technical delivery experience, with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS environments
• You communicate clearly and credibly with engineering peers, customer architects, and executive stakeholders
• You have a degree in Computer Science or a related field
• 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’ve mentored technical talent and created reusable assets — frameworks, playbooks, internal tooling
• You have deep experience in data modeling, processing, and analytics, with demonstrable proficiency across platforms like Salesforce Data 360, Snowflake, or Databricks
• Salesforce certifications (Administrator, Platform Developer I/II, Agentforce Specialist, System Architect)
• Familiarity with DevOps/CI-CD practices, observability tooling, or data governance frameworks
• Track record of influencing enterprise software product roadmaps through field engineering insight
• Experience architecting multi-cloud, multi-system enterprise AI solutions for Global 500 customers
• Open-source contributions, published technical writing, or conference presentations