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Careers

Help us turn planning into something faster.

Planlift converts 2D drawings into AI-generated 3D visuals in seconds. We're a small team building something architects, planners and developers actually use. Three roles open now.

01Leadership

Chief Technology Officer

London / RemoteFull-timeFounding team

Planlift is looking for a founding CTO who wants to build something from scratch rather than inherit someone else's architecture. You would be the first technical decision-maker at the company, working directly with the founding team to set the direction of the product and the engineering culture that grows around it.

The problem is a real one. Architects, planners and developers spend days creating presentation visuals for projects that are still in early concept. We compress that into seconds. You would own the systems that make that possible, from image generation pipeline to the web platform professionals use daily.

This fits someone who has been in a senior engineering role and wants ownership they have not had yet, or a technical co-founder who knows exactly what they would do differently this time.

What you'll own

  • Technical architecture across the web platform, AI image generation pipeline, and infrastructure from day one
  • Hiring and shaping the engineering team, starting with the Senior Developer and ML Engineer roles below
  • Engineering roadmap built in close collaboration with the founders, with real influence over product direction
  • Technical conversations with investors and partners as the company grows
  • The engineering standards the company will still be working within five years from now

What we're looking for

  • 8+ years in software engineering with at least one genuine technical leadership role on your record
  • Experience building AI-powered or media-processing SaaS products; PropTech, DesignTech, or creative tools background is a meaningful advantage
  • Comfortable across the full stack; you can evaluate architectural tradeoffs even where you would not write every line yourself
  • You have shipped products under genuine uncertainty before, and you have a clear sense of what good enough looks like at each stage
  • You can explain a technical decision to a non-technical founder without losing precision or patience

02Engineering

Senior Full-Stack Developer

London / RemoteFull-timeEarly hire

This is a hands-on role for a senior engineer who wants to build something close to zero. You would be among the first engineering hires, working with the CTO to ship the core product and set the technical patterns the team will scale into.

The product has real surface area: file uploads, rendering queues, credit systems, user accounts, a generation interface, and a sharing layer. It needs to be fast, reliable and clear under real professional use. That requires engineering judgment, not just feature execution.

If you want to move into pure management in the next year, this is probably not the right fit. If you want to be the person who set the architectural tone and can still point to the commits five years later, keep reading.

What you'll build

  • The web application used daily by architects, planners and developers: upload flows, generation interface, gallery, and share pages
  • Backend services and APIs in Python or Node.js handling file processing, rendering queues, and third-party integrations
  • Database design and query performance across relational and object stores
  • Integration with the ML pipeline to surface AI-generated visuals cleanly inside the main product
  • Testing standards, CI/CD, and deployment infrastructure in a cloud environment

What we're looking for

  • 5+ years of professional development with real experience on both the frontend and backend sides of a product
  • Strong React or Next.js skills; you think in components but you also think in users
  • Python or Node.js on the backend; you have opinions about API design and you can defend them
  • PostgreSQL and a track record of writing queries that perform at scale
  • You can take a feature from spec to production with minimal hand-holding and without leaving a mess behind
  • Experience with file processing, media pipelines, or async job queues is a genuine asset

03Machine Learning

Machine Learning Engineer

London / RemoteFull-timeEarly hire

Planlift takes a 2D drawing and returns a photorealistic 3D visual. The magic in the middle is what this role is about. We automatically write the generation prompt from the uploaded drawing, handle conditioning on the drawing's structure, and tune the output for architectural and planning contexts specifically. You would own that system.

This role is for an ML engineer who is drawn to hard applied problems rather than benchmark competitions. Our outputs need to be good enough for professional use, which means they have to look correct, read as plausible architecture, and remain faithful to the original drawing. That is a more constrained problem than open image generation, and a more interesting one.

The design and planning expertise is at the table. What we need is someone who can translate that into models that work reliably in production, not just in notebooks.

What you'll build

  • The prompt generation system that automatically writes conditioning prompts from user-uploaded drawings without requiring any prompt engineering from the user
  • Fine-tuning and evaluation frameworks for image generation models adapted to architectural and planning output specifically
  • ControlNet-style conditioning pipelines that preserve drawing structure through the generation process
  • Quality scoring and filtering systems to ensure outputs meet the bar for professional use
  • Production ML infrastructure that integrates cleanly into the main web platform and returns results in seconds

What we're looking for

  • 3+ years working with image generation or computer vision models in production, not just in research
  • Strong Python and fluency with the diffusion model ecosystem: Stable Diffusion, ControlNet, SDXL, or close equivalents
  • Experience fine-tuning generative models on domain-specific datasets and evaluating output quality at scale
  • You understand the tradeoffs between fine-tuning, LoRA, ControlNet conditioning, and prompt engineering and you have made those calls before under real constraints
  • Comfortable owning the full ML lifecycle: from data curation and labeling through deployment and monitoring
  • Architecture, spatial, or planning domain familiarity is a strong advantage

Don't see your role? Get in touch.