At a Glance
- Tasks: Build and scale AI agents that power real businesses on our innovative platform.
- Company: Join DeepFlow, a pioneering tech company transforming AI-native businesses.
- Benefits: Competitive salary, significant equity, and fully remote work with flexible hours.
- Why this job: Make a real impact in AI while working with an exceptional team of industry leaders.
- Qualifications: Strong software engineering skills, experience with AI tools, and full-stack capabilities.
- Other info: Fast hiring process with immediate openings and excellent career growth opportunities.
The predicted salary is between 120000 - 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 City of London employer: DeepFlow
Contact Detail:
DeepFlow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Engineer (AI) in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and tech space, especially those who are already working at DeepFlow or similar companies. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve built any cool projects or have experience with AI tools, make sure to showcase them. A portfolio or GitHub repo can speak volumes about your capabilities.
✨Tip Number 3
Prepare for the interview by understanding DeepFlow’s mission and the role of a Founding Engineer. Be ready to discuss how your experience aligns with building reliable AI workflows and integrating various tools.
✨Tip Number 4
Apply through our website! It’s the quickest way to get noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Founding Engineer (AI) in City of 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've shipped!
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 the Founding Engineer role. We’re looking for someone who understands AI tooling and can work with closed-source model providers, so make that clear!
Be Clear About Your Impact: When describing your past projects, focus on the impact you made. We care about how your contributions led to successful outcomes, especially in building agent workflows or integrating systems. Show us how you’ve made a difference!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the quickest way for us to get your application and start the conversation. Plus, it shows us you’re serious about joining our team at DeepFlow!
How to prepare for a job interview at DeepFlow
✨Know Your Tech Stack
Familiarise yourself with the tech stack mentioned in the job description, especially Python, TypeScript, and AWS. Be ready to discuss your experience with these technologies and how you've used them in real projects. This shows you’re not just a theoretical engineer but someone who can deliver production-quality code.
✨Showcase Your Full-Stack Skills
Prepare examples that highlight your full-stack capabilities. Discuss specific projects where you’ve built backend services and integrated them with frontend components. This will demonstrate your versatility and ability to contribute across the entire development process, which is crucial for this role.
✨Understand AI Workflows
Brush up on your knowledge of AI workflows, particularly around prompt engineering and agent evaluation. Be ready to explain what makes an agent reliable versus just a good demo. This will show that you understand the practical implications of your work and can contribute meaningfully to the team.
✨Embrace the Startup Mindset
Be prepared to discuss how you handle ambiguity and shifting priorities, as this role requires adaptability. Share experiences from previous roles where you thrived in a fast-paced environment. This will reassure the interviewers that you can keep up with the dynamic nature of a startup like DeepFlow.