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Cogna

Software Engineer

Reposted One Month Ago
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In-Office
London, Greater London, England, GBR
Mid level
In-Office
London, Greater London, England, GBR
Mid level
Build and maintain AI-first product features and internal frameworks for working with LLMs, design reusable architectures and toolchains, develop evaluation systems and benchmarks, experiment with LLM techniques, and take experimental ideas into production while writing high-quality maintainable code.
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About Cogna

Physical industries like energy, utilities, and infrastructure underpin our economy and daily lives. Yet many of the organizations responsible for them are constrained by fragmented processes, fragile legacy systems, and decades-old ways of working.

These organizations must manage aging assets, deliver major infrastructure programs, meet tighter standards, and keep essential services running. Cogna helps them solve the operational problems that slow this work down. Our AI platform captures the context behind complex workflows and turns it into AI-native applications that help teams work faster, more accurately, and more reliably.

Since our launch in May 2023, we've seen very strong 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. We're a team of around 80 today, on a path to Series B and scaling towards 150.

Making an impact at this scale takes people who are curious, adaptable, and motivated by purpose. 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 compiler theory, code analysis, or domain-specific languages

We do not require a specific number of years of experience. We accept candidates with career breaks and CV gaps. Life happens. Please apply anyway.

What We Offer

  • Competitive salary & share option plan
  • 25 days annual leave + public holidays
  • 7.5% company pension contribution
  • Private healthcare (including family cover and pre-existing conditions)
  • Regular socials and offsites; access to on-site gym & classes

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