About this role
Senior Forward Deployed Engineer driving end-to-end architecting and deployment of agentic AI solutions for Salesforce's enterprise customers. You’ll lead technical delivery, mentor engineers, and establish engineering standards, partnering with Deployment Strategists to translate customer needs into production-grade AI deployments.
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 enterprise integration patterns. 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 technical blockers that other engineers can't — data integration failures, model deployment issues, orchestration breakdowns, performance regressions. 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 judgment on what decisions can be deferred. Codify learnings into playbooks, reusable assets, and internal frameworks for the org. Mentor other engineers through code reviews, pair sessions, and shared work. Surface field insights directly to Product and Engineering to inform the Agentforce roadmap. Partner with the Deployment Strategist to translate complex customer business challenges into agentic solutions that actually ship. Provide technical depth on at-risk or strategically critical deployments when senior engineering judgment is needed.
6+ years of software engineering or technical delivery experience with end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS. Degree in Computer Science or a related field. Expert in at least one of Python, JavaScript/TypeScript, Java, or Apex, and conversant in others. Experience integrating LLMs into production, using frameworks like LangChain or LlamaIndex, and applying prompt engineering and responsible AI practices in real customer contexts. Deep experience in data modeling, processing, and analytics, with proficiency across Salesforce Data 360, Snowflake, or Databricks. Deep Salesforce platform expertise: Agentforce, Apex, LWC, Flows, and Salesforce APIs. Entrepreneurial, get-things-done mindset with the judgment to know when "fast" is the wrong call. Mentored technical talent and created reusable assets — frameworks, playbooks, internal tooling. Strong communication and collaboration skills; able to convey complex technical concepts clearly and credibly.
Experience designing MVPs/PoCs for large enterprise customers and leading customer-facing engagements. Familiarity with deploying AI solutions in production and with building reusable internal tooling. Prior experience as a Forward Deployed Engineer or in a customer-facing technical role.