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For Companies At a Glance
- Tasks: Design and build AI workflows, integrating cutting-edge technologies for real-world applications.
- Company: Join DeepFlow, a pioneering platform scaling AI-native businesses globally.
- Benefits: Competitive salary up to £120,000, significant equity, and remote-first work culture.
- Why this job: Shape the future of AI while making a tangible impact in various industries.
- Qualifications: Strong software engineering skills with experience in AI and full-stack development.
- Other info: Dynamic startup environment with rapid growth and learning opportunities.
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
Founding Engineer (AI) employer: DeepFlow
Contact Detail:
DeepFlow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding Engineer (AI)
✨Tip Number 1
Network like a pro! Reach out to people in the AI and software engineering space, especially those who are already working at DeepFlow or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI workflows and full-stack development. This is your chance to demonstrate what you've built and how it can impact real businesses.
✨Tip Number 3
Prepare for interviews by diving deep into the tech stack mentioned in the job description. Brush up on Python, React, and any AI tools you’ve used. Being able to discuss your experience confidently will set you apart from the crowd.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of the DeepFlow team. Don’t miss out!
We think you need these skills to ace Founding Engineer (AI)
Some tips for your application 🫡
Show Off Your Skills: When you're writing your application, make sure to highlight your software engineering skills. We want to see real examples of the code you've written and the projects you've shipped. Don't just tell us about your experience; show us what you've built!
Tailor Your Application: Make your application stand out by tailoring it to the Founding Engineer role. Use keywords from the job description and relate your past experiences to the responsibilities listed. This helps us see how you fit into our vision at DeepFlow.
Be Clear and Concise: Keep your application clear and to the point. We appreciate well-structured applications that are easy to read. Avoid jargon unless it's relevant, and focus on communicating your ideas effectively. Remember, clarity is key!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to showcase your talents. Plus, it’s super easy to do!
How to prepare for a job interview at DeepFlow
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on your Python, React, and TypeScript skills, and be ready to discuss how you've used these technologies in real projects. Being able to share specific examples of your work will show that you can hit the ground running.
✨Demonstrate Your Full-Stack Capabilities
Since this role requires full-stack delivery, prepare to talk about your experience with both backend and frontend development. Have a couple of projects in mind where you’ve built features end-to-end, and be ready to explain your thought process and the challenges you faced along the way.
✨Showcase Your AI Knowledge
Familiarise yourself with modern AI tooling and be prepared to discuss your practical understanding of prompt engineering and agent evaluation. Bring examples of how you’ve shipped agent workflows to real users, as this will highlight your ability to deliver production-quality code.
✨Embrace the Startup Mindset
DeepFlow is looking for someone comfortable with ambiguity and fast-paced environments. Be ready to share experiences where you adapted to changing priorities or tackled unexpected challenges. This will demonstrate your flexibility and readiness to thrive in a startup culture.