AI Engineer

Join a pioneering force in network automation!

At IP Fabric, we enable people to uncover the truth about their networks. Built by network professionals and industry experts, our innovative solutions are transforming how enterprises manage their networks. As a post-Series B company, we're expanding rapidly across Europe, the U.S., and beyond.

We are looking for a Senior AI Engineer to build AI-native features in IP Fabric. This is a hands-on product engineering role: you will take AI features from a defined scope through to production, working on top of a uniquely rich data set — a verified digital twin of enterprise networks.

You will be building systems that run in production and create real operational value for our customers. You will work within the AI architecture and roadmap direction set by our Staff AI Engineer and product team, and you will own the delivery of what you build.

• Build and ship AI features supporting IP Fabric's network assurance use cases, including change assurance, troubleshooting, compliance, and vulnerability detection
• Own the engineering delivery of assigned AI features, from implementation through testing to production deployment
• Work with MCP and agentic frameworks to build reliable, production-grade AI capabilities
• Contribute to shared AI infrastructure, patterns, and tooling used across the AI team
• Participate in design discussions and technical reviews; raise trade-offs and risks early
• Bring forward feature ideas and technical proposals for product and the Staff AI Engineer to evaluate
• Use code assist tools (Claude Code, ChatGPT, Cursor) effectively in your daily work and share what works with your team
• Contribute to the AI Guild and share learnings within engineering

What This Role Does Not Own

• AI strategy and roadmap direction - owned by the Staff AI Engineer in partnership with product and engineering leadership
• Overall AI architecture decisions - you contribute to and influence these, and you work within them
• Research or experimentation without a path to production
• Company-wide code assist adoption programmes
• Owning the GTM relationship for AI features - you support it with technical input
• People management

• 3-5 years of experience as a software engineer
• Has built and shipped features end-to-end to production, not only prototypes or proofs of concept
• Strong software engineering fundamentals: you write clean, tested, production-ready code
• Practical experience with MCP or similar AI integration patterns
• Able to reason about trade-offs within a given design: latency, cost, reliability or availability
• Clear communicator, comfortable explaining your technical choices to engineers and to product
• Genuine, daily user of AI code assist tooling in your own development work
• Experience in network-centric, data-heavy, or infrastructure products
• Recent hands-on AI engineering experience, especially building and shipping LLM-based or agentic features to production
• Familiarity with network concepts (routing, topology, compliance frameworks)
• Exposure to MLOps or production AI operations: monitoring, cost control, regression testing
• Interest in growing toward Staff-level scope over time

Growth path

This is a Level 3 role in the IP Fabric growth framework. The natural progression is toward Level 4 (Staff), where scope expands from department-level delivery to cross-functional ownership of AI direction. We expect strong performers in this role to move in that direction, and we will be explicit about what that requires.

• 25 days of holidays + 5 flexi-days.
• Pluxee Flexi Card (up to 16 000 CZK per year).
• Anniversary rewards.
• Collaboration with diverse, international teams.
• A pet-friendly office at IP Pavlova.
• Complementary and yummy snacks, coffee, brew and refreshments.
• Regular team and company events.

Join us to experience the unique culture of a founder-led startup, where from top to bottom everyone is hands-on and has a chance to make a tangible impact on influential enterprises worldwide. Being part of IP Fabric means being part of a flexible environment that prioritizes work-life balance and growth opportunities.