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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Forward Deployed Engineer - **Company:** F5 Networks, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $58,400.0 - $80,300.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Business Systems, Software as a Service, Cloud Computing, Code Review, Encodings, Continuous Integration, Data Integrity, Information Leak Prevention, Memory Management, Github, Python (Programming Language), Key Management, Oracle (Applications), Systems Development Life Cycle, Regression Testing, Salesforce.Com, Software Engineering, Systems Integration, Management of Software Versions, Datadog, Apex Code, Enterprise Software Applications, GitHub Copilot, Large Language Models, Multi-Agent Systems, Prompt Engineering, Boomi, Zapier, Containerization, Kubernetes, Production Code, Hashicorp, Enterprise Integration, Integration Frameworks, Machine Learning Operations, Api Gateway, Restful APIs, Zendesk, Amazon Simple Queue Service (SQS), Splunk, Serverless Computing, Docker, Mulesoft, Servicenow - **Published:** September 23, 2026 - **Apply:** https://www.jofdav.com/jobs/59834193-senior-forward-deployed-engineer ## About the Role * 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 ## Description 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., 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 ## Related Videos - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)