Description
You will be a Software Engineering Lead / AI & Agentic AI Architect, responsible for architecting and building AI and agentic AI solutions. You will work with a small team of senior architects and engineers to design and operate secure microservice applications on AWS and Kubernetes. Your goal will be to establish architectural patterns and engineering practices that raise the quality and speed of AI delivery.
Your responsibilities include:
- Architecting and building AI and agentic AI solutions, including agent orchestration, tool integration, retrieval augmented generation, and autonomous workflows
- Designing and operating secure microservice applications on AWS and Kubernetes
- Establishing architectural patterns and engineering practices that other teams adopt
- Leading design and code reviews and mentoring engineers
The team builds cloud-native platforms and AI capabilities that Cisco engineers, customers, and the wider developer community rely on. You will work shoulder to shoulder with product, security, and platform teams, and own your work from architecture through live operations.
Requirements:
- Bachelor's + 12 years of related experience, or Master's + 8 years of related experience, or equivalent related work experience
- 8+ years of professional software engineering experience delivering production applications in one or more of Python, Java, Go, or JavaScript/TypeScript
- 5+ years of experience designing, deploying, and operating microservice-based applications on a public cloud platform such as AWS
- 3+ years of experience running containerized workloads in Kubernetes in a production environment
- 2+ years of hands-on experience building applications with generative AI or large language models
Preferred Qualifications:
- Master's degree in Computer Science, Engineering, or Artificial Intelligence and Machine Learning
- Experience building enterprise-scale agentic AI platforms
- Hands-on experience with agent frameworks and protocols such as LangGraph, LangChain, Model Context Protocol, or Semantic Kernel
- Experience with AI security, guardrails, policy enforcement, evaluation, and observability for AI systems in production
Benefits: No specific benefits mentioned.