Software Engineering Technical Leader
Cisco is hiring a Software Engineering Technical Leader in Budapest, Hungary. Level rates it ; you can apply on Cisco.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions LangChain, LangGraph and Semantic Kernel among its tools and skills.
- Level classes it as a lead role.
- Cisco has 1,400+ other open roles on Level.
AI in this role
Architect and build production-grade agentic AI and generative AI solutions on cloud infrastructure at Cisco.
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.
How we rate this
Software Engineering Technical Leader at Cisco rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
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?
- Tell me about a project where agentic ai was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
- Tell me about a project where microservices was part of your work. What did you do?
- Tell me about a project where cloud native was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Agentic AI, Generative AI, Microservices, and Cloud Native. 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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