Level

Solve IntelligencePosted 3mo ago

L4

Full Stack (Back-End Leaning)

Full Stack (Back-End Leaning) at Solve Intelligence scores 94 out of 100 on AI centrality, which makes it a Level 4 role on this board.

LondonFullTime$100k-$250k

AI in this role

openai
prompt-engineering

At Solve Intelligence, we aren’t just "using" AI - we are building the proprietary algorithms that define the future of Intellectual Property. We have real paying users, massive traction, and a mission to build a billion-dollar company.

🏗️ The Role: Full Stack Engineer. (Back-End Leaning)

We are looking for a super-talented engineer to help us build state-of-the-art AI products extremely fast. You will lead the development of algorithms that push the envelope of what is possible with LLMs.

What you’ll own:

  • Production-Ready AI: Develop and deploy proprietary algorithms that significantly increase the quality of generated patents.

  • SOTA Evaluation Pipelines: Build a robust, high-scale evaluation framework to benchmark our proprietary models and steer the direction of our R&D.

  • Advanced Prompt Engineering: Research and implement cutting-edge prompting methods to maximize model efficacy.

  • Full-Stack Impact: While focused on AI, you’ll work across the stack (Python, Postgres, React) to ensure our research translates into a seamless user experience.

💡 About Solve Intelligence

We are the fastest-growing startup transforming the IP landscape. Our AI platform manages everything from invention harvesting to patent generation.

  • Growth: 20-30% MoM revenue growth; selling to 600+ global IP teams (DLA Piper, tech giants, and boutiques).

  • Impact: Users report 50-90% efficiency improvements.

  • Backing: Recently featured in Sifted following our $40M Series B announcement, bringing our total funding to $55M from elite investors including Y Combinator, 20VC, Visionaries and others.

👋 Co-Founders & Team

You will work directly with a founding team of AI PhDs and elite engineers:

  • Sanj (CRO): PhD in AI (Gatsby Unit, UCL), ex-Huawei R&D, former lead at Magic Carpet AI (acquired).

  • Chris (CEO): PhD in AI (UCL), published researcher, ex-Dyson and Alan Turing Institute.

  • Angus (CTO): MEng Computer Science, ex-Qualcomm and Coremont (Brevan Howard).

🚀 Who You Are

We are a young company of highly motivated "hackers" building at a relentless pace.

  • Speed is your default: You want to put things in the hands of customers in days, not months.

  • You are a grinder: You have a strong work ethic and are willing to go the extra mile (long nights/weekends) to achieve excellence.

  • You are an optimist: You thrive in a high-energy, positive environment and take extreme ownership of your outcomes.

🛠️ What You Bring

Must-Haves:

  • Expert Python Skills: Deep experience building and shipping AI solutions.

  • Production Experience: A history of shipping algorithms and/or evaluation pipelines into live environments.

  • LLM Mastery: Practical experience with prompt engineering and modern LLM architectures.

  • Technical Versatility: Familiarity with the full stack (Postgres, TypeScript, React).

  • Clear Communication: Ability to articulate complex technical decisions clearly.

Nice-to-Haves:

  • Publications at top ML conferences (NeurIPS, ICLR, ICML).

  • Familiarity with frameworks like OpenAI Evals.

  • A history of interesting GitHub contributions or "impressively difficult" side projects.

🎁 What We Offer

  • Competitive Salary + Significant Equity: We want you to have true ownership in our success.

  • Growth: Opportunity to work with a world-class team on a genuine rocket ship trajectory.

  • Support: Full visa sponsorship and private medical insurance.

  • The Goods: Free meals and a high-performance office culture in London.

Ready to build the future of AI? Apply now. 🚀

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

Prompt EngineeringOpenAI

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. Walk me through how you've used OpenAI in your day-to-day work.
  3. How would you decide a model or AI system is ready to ship?
  4. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering and OpenAI. 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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