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For Companies At a Glance
- Tasks: Design and build AI agent frameworks, ensuring reliable workflows and integrations.
- Company: DeepFlow, a pioneering platform for scaling AI-native businesses.
- Benefits: Up to £120,000 salary, significant equity, and fully remote work.
- Why this job: Join a dynamic team and shape the future of AI with real impact.
- Qualifications: Strong software engineering skills, experience with AI models, 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.
Artificial Intelligence Engineer (m/f/d) in London employer: DeepFlow
Contact Detail:
DeepFlow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer (m/f/d) in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI field on LinkedIn or at industry events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI workflows and integrations. This is your chance to demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to AI engineering. We want to see how you think and solve problems, so be ready to showcase your thought process.
✨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 Artificial Intelligence Engineer (m/f/d) in London
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI shine through! We want to see how excited you are about building agents and working with cutting-edge technology. Share any personal projects or experiences that highlight your love for the field.
Tailor Your Application: Make sure to customise your application to fit the role of an Artificial Intelligence Engineer. Highlight your full-stack capabilities and any experience with closed-source model providers. We’re looking for specific skills, so don’t be shy about showcasing them!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and fluff. Use bullet points if it helps convey your experience and skills more effectively. Remember, we want to know what you've shipped, not just what you've done!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re in the running for this exciting opportunity. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at DeepFlow
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like Python, TypeScript, and AWS. Be ready to discuss your experience with these tools and how you've used them in real projects.
✨Showcase Your Full-Stack Skills
Prepare examples that highlight your full-stack capabilities. Discuss how you've built end-to-end solutions, from backend services to frontend features, and be ready to explain your thought process behind those decisions.
✨Understand AI Workflows
Brush up on prompt engineering and agent evaluation techniques. Be prepared to talk about what makes an AI agent reliable and how you’ve implemented these concepts in previous roles or projects.
✨Embrace the Startup Mindset
Demonstrate your comfort with ambiguity and fast-paced environments. Share experiences where you've adapted quickly to changing priorities and how you’ve contributed to a team’s success in a startup setting.