Senior Software Engineer – Agentic AI

Role Overview

• Architect and build agentic experiences: Design and implement end-to-end agentic workflows (planning, tool-use, memory, retrieval, execution, and feedback loops) that are secure, observable, and reliable in production.
• Platform-grade implementation: Deliver services/APIs that enable agentic capabilities on a multi-tenant SaaS platform, with strong guarantees around latency, scale, resiliency, and manageability.
• Safety, security, and trust: Build guardrails for agentic behavior (policy enforcement, prompt/tool security, secrets handling, auditability, abuse prevention, and data boundaries) aligned with F5’s security mission.
• Evaluation and quality: Define and automate evaluation strategies for agentic systems (offline test suites, regression harnesses, golden tasks, telemetry-driven iteration, and failure-mode analysis).
• Operational excellence: Own reliability—instrumentation, tracing, debugging, runbooks, incident response learnings, and continuous improvement for agentic services in production.
• Cross-functional leadership: Partner with Product, UX, Security, SRE, and Engineering teams across geographies to define requirements, shape roadmaps, and deliver customer value.
• Mentorship and influence: Raise engineering standards through design reviews, code reviews, technical guidance, and by modeling inclusive collaboration and ownership.

Requirements

• Typically requires 10+ years of related experience with a bachelor’s degree; or 7 + years with a master’s degree (or equivalent practical experience).
• Deep distributed systems expertise: Proven experience designing highly available, scalable services with strong operational rigor (resiliency patterns, rate limiting, backpressure, multi-region considerations).
• Strong software engineering fundamentals: Expertise in one or more of Golang, Python, Java (or similar), with production-quality coding, testing, and API design practices.
• Agentic systems experience: Hands-on experience building agentic applications/services (tool orchestration, function calling/tool APIs, RAG patterns, memory strategies, planning/execution loops, and failure recovery).
• Security mindset: Understanding of common risks and mitigations in agentic/LLM systems (prompt injection, data exfiltration, tool misuse, authorization boundaries, tenant isolation).
• Cloud-native proficiency: Experience with major cloud providers ( AWS/Azure/GCP ) and cloud-native architectures.
• Containers and orchestration: Strong experience with Docker and Kubernetes (deployment patterns, image lifecycle, service networking, scaling strategies).
• CI/CD and engineering hygiene: Git-based workflows, modern CI/CD, automated testing, and release discipline.
• Data systems: Hands-on experience with SQL and/or NoSQL technologies and designing data access patterns for scale and correctness.
• Communication and collaboration: Clear written/verbal communication; ability to align stakeholders, document decisions, and drive execution across teams.

Tech Stack

• AWS
• Azure
• Cloud
• Distributed Systems
• Docker
• Google Cloud Platform
• Java
• Kubernetes
• NoSQL
• Python
• SQL
• Go

Benefits

• Competitive salary
• Flexible working hours
• Professional development budget
• Home office setup allowance
• Global team events