F

F5

Multi-cloud app security and delivery platform

Forward Deployed Engineer 3

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • At least 8 years of software engineering experience, including at least 3 years of hands-on experience with AI/ML systems, large language model application engineering, or enterprise intelligent automation.
  • Expert Python skills, including production-quality code, REST API design, asynchronous patterns, and reusable framework design.
  • Experience shipping and operating production agentic AI and retrieval-augmented generation systems, including retrieval strategy, evaluation design, and their failure modes.
  • A strong enterprise business systems background, with hands-on Salesforce experience (Flows, Apex, CPQ, and/or Agentforce/Einstein) and familiarity with Oracle application stacks.
  • Experience with enterprise integration platforms such as MuleSoft, Workato, or Boomi across distributed software-as-a-service ecosystems.
  • Experience with cloud platforms such as AWS, GCP, or Azure; containerization with Docker or Kubernetes; continuous integration and continuous delivery with GitHub Actions or equivalent; secrets management; and least-privilege access.
  • Daily hands-on use of AI coding and productivity tools in the candidate's own workflow.
  • Working knowledge of go-to-market, revenue operations, and customer experience business processes, and ability to turn a vague business request into a scoped technical design.
  • Ability to prototype, measure shipped work, and drive problems through resolution.

Responsibilities

  • Prototype and ship internal tools that improve team throughput, including AI-assisted coding workflows, automated code review, test generation and quality assurance automation, and AI drafting of product requirements documents, user stories, and acceptance criteria.
  • Move ideas from scope to minimum viable product quickly, build and demonstrate them, onboard real users, then decide whether to harden or discontinue them.
  • Roll out and tune AI developer platforms such as Claude Code, Gemini Enterprise, and GitHub Copilot across engineering teams, including standards, prompt and context patterns, guardrails, and adoption.
  • Measure tools through outcomes such as cycle time, review latency, defect escape rate, and hours saved.
  • Design and deliver AI automation across business systems, including go-to-market and revenue operations 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, including multi-agent orchestration, tool calling, memory management, human-in-the-loop checkpoints, and stateful workflow design.
  • Architect enterprise retrieval-augmented generation over business and product data, including ingestion and chunking strategy, vector store selection, hybrid search and reranking, embedding model management, and evaluation loops tied to business key performance indicators.
  • Establish prompt engineering practices including versioning, structured output contracts, regression test harnesses, and systematic evaluation.
  • Lead integration design across Salesforce (Flows, Apex, Agentforce/Einstein), Oracle applications, ServiceNow or Zendesk, MuleSoft or Workato, and internal application programming interfaces.
  • Build a reusable connector library and self-service intake path so new use cases can be onboarded without bespoke work each time.
  • Own continuous integration and continuous delivery for AI workloads, including automated evaluation gates, model and prompt versioning, deployment orchestration, and rollback strategy.
  • Maintain production AI observability and reliability through monitoring, alerting, and data integrity practices using Datadog, Splunk, or equivalent.
  • Define AI engineering standards for the customer experience organization, including coding patterns, retrieval-augmented generation design, evaluation 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 to ensure systems meet security, privacy, and AI ethics requirements; identify and mitigate model bias and deliberately address personally identifiable information and prompt injection risks.
  • Present architectures, trade-offs, and return on investment clearly to senior leadership and non-technical partners.

Desired Qualifications

  • Oracle and/or Salesforce development at enterprise scale; Architect-level certification.
  • Large language model security experience, including prompt injection defense, data leakage prevention, output filtering, and personally identifiable information handling in production pipelines.
  • ServiceNow or Zendesk AI experience for intelligent IT service management automation, including auto-triage, severity classification, and service-level agreement routing.
  • Experience with AWS serverless and integration services, including Lambda, API Gateway, Step Functions, EventBridge, and SQS.
  • Experience with HashiCorp Vault, AWS Secrets Manager, or similar secrets tooling.
  • Experience in a platform engineering, shared services, or federated AI operating model.

About the Company

F5

Multi-cloud app security and delivery platform

F5 provides multi-cloud application services and security, including web application and API protection (WAF and API security), bot defense, fraud prevention, and application delivery (load balancing and access management). Its products protect and accelerate applications wherever they run, delivered as licenses, subscriptions, and support contracts, with professional services to help implementation. The company differentiates itself with a broad, integrated suite that covers both security and delivery across multi-cloud environments for a wide range of industries. Its goal is to help customers securely deliver reliable, fast, and available applications across any cloud or data center while reducing fraud and ensuring smooth user access.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Seattle, WA
Founded
1996

Recently Posted Jobs

Explore more opportunities at F5

See more jobs