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F5 is executing an enterprise-scale Agentic AI transformation and seeks a Senior AI Software Development Engineer to lead the implementation and optimization of high-code agent development frameworks and enterprise AI integrations. This is a highly technical, hands-on role focused on building scalable agentic systems with robust engineering standards.
Key responsibilities include:
**Agentic Architecture & Orchestration**: Design and optimize enterprise-grade agent orchestration frameworks supporting tool use, memory, RAG, and agentic workflows. Develop patterns for multi-agent collaboration, event-driven execution, and workflow chaining across enterprise systems. Implement standards for agent lifecycle management, state persistence, and context engineering.
**Gemini & Vertex AI Integration**: Integrate Gemini models via Vertex AI with secure, scalable API consumption and robust model routing. Develop internal SDKs, abstractions, and reusable components to standardize Gemini usage. Implement prompt engineering, token efficiency, grounding strategies, and structured output patterns.
**High-Code Agent Enablement**: Develop reference implementations and reusable libraries for high-code agents in Java, Python, Go, or TypeScript. Implement secure integration patterns for agents interacting with Salesforce, Snowflake, SharePoint, ServiceNow, and internal APIs. Build and maintain MCP servers and secure API integration gateways.
**Observability, Safety & Governance**: Build logging, tracing, telemetry, and evaluation pipelines for agent performance. Apply safety guardrails including input/output validation, hallucination mitigation, and prompt injection defenses. Collaborate with Security on data handling and compliance.
**Developer Enablement**: Guide engineering teams adopting Gemini Code Assist and internal AI platforms. Create technical documentation, libraries, and code samples. Participate in code reviews.
**Performance & Scalability**: Optimize inference latency, parallelization, and cost management. Implement caching, streaming, and batching techniques. Conduct performance testing and benchmarking.
Required: 7+ years software engineering with distributed systems and backend architecture expertise. Deep hands-on coding in Python plus Go, Java, or TypeScript. Production experience with LLM-based systems, prompt engineering, tool calling, RAG, embeddings, and agent frameworks. Experience with Vertex AI, Gemini APIs, or similar enterprise AI platforms. Strong API design, microservices, and cloud-native architecture knowledge. Experience with orchestration frameworks like LangChain or LlamaIndex. Familiarity with vector databases and enterprise security patterns.
