Software Engineer

About the role

About Cogna We live in a world that runs on physical industries like energy, logistics, manufacturing. These sectors are essential to our economy and daily lives, yet they are held back by inefficiencies, fragile legacy systems, and decades-old ways of working. This is not just a business problem; it is a societal one. When grids fail, supply chains stall, or factories falter, entire economies are disrupted. These companies face unique, complex challenges that typical software was never designed to solve. Cogna was founded to change this. Our mission is to give critical industries their own AI-powered Software Factory: a way to build and deploy bespoke digital tools that solve pressing operational challenges. Since our launch in May 2023, we've seen incredible customer traction and revenue growth. We're backed by leading VCs, including Notion Capital and Hoxton Ventures, and we're building a world-class team to take on one of the most important challenges of our time. Tackling challenges at this scale takes people who are curious, adaptable, and motivated by impact. If our mission resonates with you, we encourage you to apply, even if your experience doesn't match every requirement. We are committed to building a diverse team that reflects the industries and societies we serve. The Role We're looking for a Software Engineer who is genuinely excited about building with AI, not just building AI features. You'll work at the frontier of agentic systems, helping to develop the platform that understands customer problems, defines requirements, and generates and verifies software to address them. The right person has strong engineering fundamentals, a problem-solving mindset, and uses AI tools as a core part of how they build every day. We care less about where you've worked or how many years you've been in the industry, and more about what you've built, how you think, and whether you have genuine curiosity about what's happening at the edge of software engineering. We've been building AI-first products for enterprise customers since the early days of GPT-3.5. We have mature internal frameworks for evaluation, verification, code generation, agentic behaviour, RAG, observability, and orchestration. You'll be contributing to these and using them to build the core intelligence of our platform. What You'll Do Build and maintain reliable AI-first product features, including internal frameworks and tooling for working with LLMs Use AI coding tools (Cursor, Claude, and similar) as a genuine part of your daily workflow to build and ship faster Experiment with AI and LLM techniques, models, and approaches to improve the accuracy and reliability of our outputs Design and build reusable application architectures and toolchains, working closely with the software synthesis team Build and improve evaluation systems and benchmarks Take ideas from experimentation to production. You know what a great product looks like and how to get there Write high-quality, efficient, and maintainable code. You know how to move fast without creating the kind of tech debt that slows a team down later Contribute to an engineering culture that balances innovation with reliability What We're Looking For Must-haves Strong CS fundamentals: you understand architectural trade-offs, scalability, and maintainability. You can make sound long-term engineering decisions and critically evaluate AI-generated code rather than just accepting it. AI-native workflow: you use AI coding tools as a core part of how you work, not occasionally. You have a clear view of where they help and where they fall short. LLM experience: either professional or personal. You've worked with LLM APIs and understand the fundamentals of building reliable systems on top of them. RAG, evaluation pipelines, and observability tooling are familiar territory. Python proficiency: our stack is primarily Python and Node. You're comfortable in complex Python codebases and understand the ecosystem well. Startup mindset: you take ownership without being asked, are comfortable with ambiguity, and can balance speed with sound engineering judgment. You understand that what you build today someone will have to maintain tomorrow. Doer mentality: you get your hands dirty across any kind of problem, not just the ones in your immediate scope. We are a small team and we expect people to move with urgency, pick up what needs solving, and care about the outcome, not just the task. Strong signals we look for Active side projects, open source contributions, or a GitHub that shows you build things outside of work Hands-on experimentation with new AI tools and models before they become mainstream Experience owning features end to end, not just executing against a spec Evidence of growing into architectural decisions over time, not just rapid prototyping Familiarity with Go or Rust, or modern frontend development Experience with workflow orchestration (Argo, Temporal), Kubernetes, or CI/CD tooling Background in

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