Senior AI Engineer

F5 Networks, Inc.
San Jose, United States of America
11 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 265K

Job location

San Jose, United States of America

Tech stack

Java
API
Artificial Intelligence
Application Frameworks
Cloud Engineering
Encodings
Data Security
Distributed Systems
JSON
Python
Software Architecture
Role-Based Access Control
Software Safety
Salesforce
SharePoint
Software Engineering
Systems Integration
TypeScript
AI Infrastructure
Data Logging
Large Language Models
Snowflake
Multi-Agent Systems
Prompt Engineering
Model Validation
AI Platforms
Kubernetes
Optimization Algorithms
low-code
Api Design
Software Coding
Automation Anywhere
ServiceNow
Go
Microservices

Job description

This is a deeply technical individual contributor role. The Principal Engineer will design and implement scalable agentic systems, establish engineering standards for AI workflows, and enable engineering teams to build production-ready agents using Gemini, Vertex AI, and internal AI infrastructure., Agentic Architecture & Orchestration

  • Design and implement enterprise-grade agent orchestration frameworks supporting tool use, memory, RAG, agentic workflows and automation.
  • Establish patterns for multi-agent collaboration, event-driven execution, and workflow chaining across enterprise systems.
  • Define standards for agent lifecycle management, state persistence, and context engineering.

Gemini & Vertex AI Integration

  • Lead technical integration of Gemini models via Vertex AI, ensuring secure, scalable API consumption and proper model routing.
  • Develop internal SDKs, abstractions, and reusable components to standardize Gemini usage across F5 teams.
  • Optimize prompt engineering, token efficiency, grounding strategies, and structured output patterns., * Build reference implementations and reusable frameworks for high-code agents in Java, Python, Go, or TypeScript.
  • Establish secure integration patterns for agents interacting with Salesforce, Snowflake, SharePoint, ServiceNow, and internal APIs.
  • Drive best practices for MCP (Model Context Protocol) server development and secure API mediation.

Observability, Safety & Governance

  • Implement logging, tracing, telemetry, and evaluation pipelines for agent performance and reliability.
  • Establish guardrails including input/output validation, hallucination mitigation, prompt injection defenses, and policy enforcement.
  • Partner with Security to ensure secure data handling, RBAC enforcement, and compliance alignment.

Developer Enablement & Technical Leadership

  • Support engineering teams adopting Gemini Code Assist, CLI workflows, and internal AI development platforms.
  • Create technical documentation, internal libraries, and code samples for no-code, low-code, and pro-code agent builders.
  • Provide architectural review and guidance for AI-enabled applications across F5.

Performance & Scalability

  • Optimize inference latency, parallelization, and cost management strategies across agent workflows.
  • Implement caching strategies, streaming responses, and batching techniques to improve throughput and reliability.
  • Evaluate and benchmark agent/model performance across different workloads., A successful Principal Software Development Engineer in this role will:
  • Deliver a secure, scalable orchestration layer for enterprise agents.
  • Enable engineering teams to build production-grade high-code agents with consistent architecture patterns.
  • Establish strong observability, evaluation, and safety controls for AI-driven workflows.
  • Accelerate AI agents rollout by providing reusable integrations, SDKs, and reference implementations.
  • Serve as the technical authority for enterprise agentic AI engineering at F5.

Impact

  • This role will directly shape how F5 builds and scales agentic AI across engineering, sales, support, finance, and product teams.
  • You will define the technical foundation that enables no-code, low-code, and pro-code AI development while ensuring enterprise-grade reliability, governance, and security.

The Job Description is intended to be a general representation of the responsibilities and requirements of the job. However, the description may not be all-inclusive, and responsibilities and requirements are subject to change.

The annual base pay for this position is: $176,800.00 - $265,200.00

F5 maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, geographic locations, and market conditions, as well as to reflect F5's differing products, industries, and lines of business. The pay range referenced is as of the time of the job posting and is subject to change.

Requirements

The ideal candidate has strong distributed systems expertise, deep familiarity with LLM architectures and agent frameworks, and the ability to translate AI theory into secure, production-grade implementations., * 10+ years of experience in software engineering, with significant experience in distributed systems and backend architecture.

  • Deep hands-on coding expertise in Python and at least one of: Go, Java, or TypeScript.
  • Production experience with LLM-based systems, including prompt engineering, tool calling, RAG, embeddings, and agent frameworks.
  • Experience with Vertex AI, Gemini APIs, OpenAI APIs, or similar enterprise AI platforms.
  • Strong understanding of API design, microservices, Kubernetes, and cloud-native architectures.
  • Experience building or integrating orchestration frameworks (e.g., LangChain, LlamaIndex, custom orchestration layers).
  • Familiarity with vector databases, embedding pipelines, and retrieval strategies.
  • Strong understanding of authentication, authorization, and enterprise security patterns.
  • Proven ability to build reusable platforms, not point solutions., * Experience building multi-agent systems or autonomous workflow engines.
  • Experience with model evaluation pipelines and AI quality metrics.
  • Familiarity with structured output enforcement (JSON schemas, function calling).
  • Experience working with enterprise data systems such as Snowflake, Salesforce, ServiceNow, SharePoint.
  • Knowledge of cost modeling and inference optimization techniques.
  • Experience contributing to internal developer platforms or SDK ecosystems.
  • Background in AI safety, red-teaming, or model robustness evaluation.

About the company

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.

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