Senior Forward Deployed Engineer

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation.  Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive. Senior Forward Deployed Engineer F5 Digital · Customer Experience Organization   About the Role   The F5 CX Organization builds and runs the enterprise systems behind GTM, Customer Success & Support, RevOps, and Platform Engineering. We are embedding AI into how those systems work, and into how we build them.  We are hiring a Senior Forward Deployed Engineer : a hands-on senior individual contributor who moves from business problem to working prototype fast, then hardens what works into production. Your time splits across two mandates: maturing our enterprise applications with AI and automation, and making our own engineering and product teams measurably faster with AI across the SDLC.  This is a greenfield build role, not a sustain-the-business role. You will set the technical patterns other engineers follow.  What You'll Do   AI for the SDLC & Internal Productivity   Prototype and ship internal tools that raise team throughput: AI-assisted coding workflows, automated code review, test generation and QA automation, and AI drafting of PRDs, user stories, and acceptance criteria  Go from idea to MVP in days. Scope it, build it, demo it, get real users on it, then decide to harden or kill  Roll out and tune AI developer platforms (Claude Code, Gemini Enterprise, GitHub Copilot, or equivalent) across engineering teams, including standards, prompt and context patterns, guardrails, and adoption  Instrument what you build. Cycle time, review latency, defect escape rate, and hours saved, reported as outcomes rather than activity  Enterprise Applications & Agentic Systems   Design and deliver AI automation across business systems: GTM and RevOps copilots, support triage and resolution, quote-to-cash automation, and end-to-end process workflows  Build production agentic systems with LangChain, LangGraph, MCP, or equivalent: multi-agent orchestration, tool calling, memory management, human-in-the-loop checkpoints, and stateful workflow design  Architect enterprise RAG over business and product data: ingestion and chunking strategy, vector store selection, hybrid search and reranking, embedding model management, and eval loops tied to business KPIs  Establish prompt engineering as an engineering discipline: versioning, structured output contracts, regression test harnesses, and systematic evaluation  Integrations & Platform Engineering   Lead integration design across Salesforce (Flows, Apex, Agentforce/Einstein), Oracle applications, ServiceNow/Zendesk, MuleSoft/Workato, and internal APIs  Build the reusable connector library and self-serve intake path so new use cases onboard without bespoke work every time  Own CI/CD for AI workloads: automated eval gates, model and prompt versioning, deployment orchestration, and rollback strategy  Keep production AI observable and reliable through monitoring, alerting, and data integrity practices (Datadog, Splunk, or equivalent)  Technical Leadership & Responsible AI   Define AI engineering standards for the CX organization: coding patterns, RAG design, eval practices, integration patterns, and documentation  Mentor AI, automation, and prompt engineers through design reviews, pair engineering, and structured feedback  Partner with Enterprise Architecture and governance review boards so systems meet security, privacy, and AI ethics requirements. Identify and mitigate model bias, and handle PII and prompt injection risk deliberately  Present architectures, trade-offs, and ROI clearly to senior leadership and non-technical partners  What You'll Bring   8+ years of software engineering experience, including 3+ years hands-on with AI/ML systems, LLM application engineering, or enterprise intelligent automation  Expert Python: production-quality code, REST API design, async patterns, and reusable framework design  Production agentic AI and RAG systems you have shipped and operated, not demos. Fluency with retrieval strategy, eval design, and the failure modes of both  Strong enterprise business systems background, with hands-on Salesforce (Flows, Apex, CPQ, and/or Agentforce/Einstein) and familiarity with Oracle application stacks  Experience with enterprise integration platforms (MuleSoft, Workato, Boomi, or equivalent) across distributed SaaS ecosystems  Cloud platforms (AWS, GCP, or Azure), containerization (Docker/Kubernetes), CI/CD (GitHub Actions or equivalent), secrets management, and least-privilege access  Daily hands-on use of AI coding and productivity tooling in your own workflow  Working knowledge of GTM, RevOps, and CX business processes, with the ability to turn a vague business ask into a scoped technical design  A bias toward shipping: you prototype to learn, measure what you ship, and drive problems to resolution without waiting for permission  Nice to Have   Oracle and/or Salesforce development at enterprise scale; Architect-level certification  LLM security: prompt injection defense, data leakage prevention, output filtering, PII handling in production pipelines  ServiceNow or Zendesk AI for intelligent ITSM automation: auto-triage, severity classification, SLA routing  AWS serverless and integration services (Lambda, API Gateway, Step Functions, EventBridge, SQS)  HashiCorp Vault, AWS Secrets Manager, or similar secrets tooling  Experience in a platform engineering, shared services, or federated AI operating model