At a Glance
- Tasks: Build and scale AI-native businesses with cutting-edge technology and innovative workflows.
- Company: Join DeepFlow, a pioneering platform transforming AI business operations.
- Benefits: Competitive salary, significant equity, and fully remote work opportunities.
- Other info: Work alongside industry leaders and enjoy exceptional career growth in a dynamic team.
- Why this job: Make a real impact by shaping the future of AI in a fast-paced startup environment.
- Qualifications: Strong software engineering skills, experience with AI tools, and full-stack capabilities.
The predicted salary is between 100000 - 120000 £ per year.
Location: Remote first (global, UK timezone)
Compensation: Up to £120,000 + significant equity
Type: Full-time
What is DeepFlow?
DeepFlow is the hyperscaling platform. We launch and scale AI-native businesses. An operator with 10 years of domain expertise pairs with DeepFlow’s platform and engineering support to build a business that would previously have needed a team of 50. You’re building the agents that make it work.
Where we are now
- Platform live with paying customers across law, finance, recruitment, and media
- Launching our founding cohort through DeepFlow Foundry: deploying agents into real revenue-generating businesses
- Preparing for a significant raise to scale from 2–3 companies to 10+ by September, with a roadmap to 100 in 2027
- Research team published at AAAI 2026 (invited oral) and DAI 2025, with work adopted by top global universities and companies
The Role
You own the agent layer. Every AI workflow that runs on DeepFlow - the scaffolding, the prompts, the tool integrations, the evaluation pipeline - is your responsibility. Your decisions about agent architecture, provider selection, and quality assurance directly determine whether our companies’ AI delivers in production. This is a software engineering role with an agent specialisation. You’re a full-stack engineer first - you write backend services, build APIs, and ship features end-to-end. Your focus is the model layer, but you’re not siloed to it. You work directly with the CTO/CPO and CSO to shape product direction. Significant equity reflects the scope and impact of the position.
What You’ll Build
- Agent Scaffolding: Designing and building the frameworks that connect LLMs into reliable, production-grade workflows - prompt engineering, tool use, and multi-step chains that hold up at scale.
- Provider Integration: Working with closed-source providers (OpenAI, Anthropic, Google, etc.) via OpenRouter. Managing model selection, fallbacks, cost optimisation, and latency across providers.
- Agent Evaluation: Building the eval infrastructure that measures whether agents actually work - regression testing, quality metrics, and structured failure analysis.
- Integration Engineering: Connecting agents to the external world: Slack, GSuite, CRMs, accounting tools, and domain-specific APIs. The integration layer that makes agents useful in real businesses.
- Full-Stack Delivery: You write backend services, build API endpoints, and contribute to the frontend when needed. Agents don’t exist in a vacuum - this is still a software engineering role.
- Product Direction: You work closely with the founding team to translate cohort feedback and client needs into agent architecture decisions. What to build matters as much as how you build it.
What We’re Looking For
- Strong software engineer first. You write clean, production-quality code and you ship fast. Real deployed systems, not notebooks.
- Experience building with closed-source model providers in production - shipping agent workflows to real users, not just prototyping.
- Practical understanding of prompt engineering, tool use, and agent evaluation. You know what makes an agent reliable versus what makes a good demo.
- Full-stack capable. Backend (Python), infrastructure basics, and enough frontend (React/TypeScript) to ship features end-to-end.
- Fluent with modern AI tooling - you use Cursor, Claude Code, or similar daily and it makes you faster. AI tooling is not optional here.
- Comfortable with ambiguity and startup pace. Priorities shift weekly based on cohort feedback.
- Right to work in the UK permanently.
We care less about
- Your degree (or lack of one)
- How many years you’ve been working - we care about what you’ve shipped
- Whether you’ve published papers - this is an engineering role, not a research role
Tech Stack
- Backend & Agents: Python, pydantic-ai, proprietary agent frameworks, OpenRouter
- Frontend: TypeScript, React, Vite
- Infrastructure: AWS (EKS), Docker, Inngest (event-driven orchestration)
- Tools: Cursor, Claude Code, GitHub
Why Join
- Ownership: Significant equity as a founding engineer. The agents you build power every business on the platform.
- Real traction: Paying customers, founding cohort live, and a significant raise in preparation. What you build in the next 6–12 months directly determines whether we hit 10 companies by September.
- Exceptional team: Co-founder who sold his AI company to WPP for $100M. Product leader who scaled a Meta platform to 400K+ users. Research team published at top AI venues with work adopted by leading universities and Fortune 500 R&D teams. Advisors include a leading NLP researcher and a Google DeepMind team lead.
- Flexibility: Fully remote, UK timezone. Regular offsites. We care about what you ship, not when you’re online.
We’re hiring immediately. The process is fast: we make offers within one week.
Founding Engineer (AI) in London employer: DeepFlow
DeepFlow is an exceptional employer for those looking to make a significant impact in the AI space. As a founding engineer, you will enjoy substantial equity and the opportunity to shape the future of AI-native businesses while working with a talented team that has a proven track record in the industry. With a fully remote work culture that prioritises flexibility and innovation, DeepFlow offers a unique environment where your contributions directly influence the success of real revenue-generating projects.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Engineer (AI) in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and software engineering space, especially those connected to DeepFlow. Use LinkedIn or even Twitter to engage with industry leaders and show your interest in their work.
✨Tip Number 2
Prepare for those interviews! Brush up on your full-stack skills, especially Python and React. Be ready to discuss your past projects and how you’ve tackled challenges in building reliable AI workflows.
✨Tip Number 3
Showcase your passion for AI! Create a portfolio that highlights your experience with closed-source model providers and any cool projects you've worked on. This will help us see your hands-on experience and creativity.
✨Tip Number 4
Apply through our website! It’s the quickest way to get noticed. Make sure to tailor your application to highlight how your skills align with what we’re looking for in a Founding Engineer.
We think you need these skills to ace Founding Engineer (AI) in London
Some tips for your application 🫡
Show Your Engineering Skills:Make sure to highlight your software engineering experience in your application. We want to see examples of clean, production-quality code you've written and any real systems you've deployed. This is your chance to show us what you can ship!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific skills and experiences that match our job description. We love seeing how your background aligns with what we’re looking for in a Founding Engineer.
Be Clear About Your AI Experience:Since this role involves working with AI workflows, make sure to detail your experience with closed-source model providers and any practical knowledge of prompt engineering. We want to know how you’ve made agents reliable in production settings.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process. Let’s get started on this journey together!
How to prepare for a job interview at DeepFlow
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description, especially Python, TypeScript, and React. Brush up on your experience with closed-source model providers and be ready to discuss how you've shipped real deployed systems.
✨Showcase Your Full-Stack Skills
Prepare to demonstrate your full-stack capabilities. Be ready to talk about your backend services, API development, and any frontend work you've done. Highlight specific projects where you’ve integrated various components to deliver a complete solution.
✨Understand AI Workflows
Familiarise yourself with prompt engineering and agent evaluation. Be prepared to discuss what makes an agent reliable versus just a good demo. Bring examples of how you've built or improved AI workflows in previous roles.
✨Embrace the Startup Mindset
Since this role is in a fast-paced startup environment, be ready to discuss how you handle ambiguity and shifting priorities. Share experiences where you adapted quickly to feedback or changes in direction, showcasing your flexibility and problem-solving skills.
