Mistral AISingapore4h ago
CiscoPosted 1w ago
Software Engineering Technical Leader at Cisco scores 93 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Software Engineering Lead / AI & Agentic AI Architect
Meet the Team
Our team builds the cloud-native platforms and AI capabilities that Cisco engineers, customers, and the wider developer community rely on every day. We take emerging AI and agentic technology and turn it into production systems rather than demonstrations, which is where most organizations still stall. The team is a small and senior group of architects and engineers who work shoulder to shoulder with product, security, and platform teams, and who own their work from architecture through live operations. Debate here is direct and technical, and the person with the better argument wins regardless of title. Agentic AI is moving faster than any technology this team has worked with, and the decisions made here shape how Cisco adopts it safely.
Your Impact
Architect and build AI and agentic AI solutions, including agent orchestration, tool integration, retrieval augmented generation, and autonomous workflows, so that emerging capability reaches customers as dependable product rather than experiment. Design and operate secure microservice applications on AWS and Kubernetes, applying a security-first approach across application, API, container, identity, and data layers to protect enterprise data as system autonomy increases. Establish architectural patterns and engineering practices that other teams adopt, raising the quality and speed of AI delivery well beyond this group. Lead design and code reviews and mentor engineers, so that sound technical judgment scales further than any one person can reach. Success in this role looks like agentic systems running in production with clear guardrails, measurable reliability, and engineers across the organization building on the patterns you set.
Minimum Qualifications
- Bachelors + 12 years of related experience, or Masters + 8 years of related 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, including at least one production system using retrieval augmented generation, embeddings, or tool and function calling.
Preferred Qualifications
- Master's degree in Computer Science, Engineering, or Artificial Intelligence and Machine Learning.
- Experience building enterprise-scale agentic AI platforms, including agent orchestration and multi-agent workflows.
- 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.
- Proven ability to mentor engineers and influence architecture decisions across organizational boundaries without direct authority, evidenced through patents, publications, open-source contributions, or major engineering initiatives.
At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.
Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.
We are Cisco, and our power starts with you.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through how you've used LangChain in your day-to-day work.
- What are the limits of LangGraph that you've run into, and how did you work around them?
- What's a project where you used Semantic Kernel hands-on?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: Rag, LangChain, LangGraph, and Semantic Kernel. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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