Full Stack Engineer

Capsa AI
London
11 months ago
Applications closed

Related Jobs

View all jobs

Full Stack Data Engineer (Client Facing)

Full Stack Data Engineer (Client Facing)

Full stack Data Engineer

Senior Full Stack Data Engineer (Client Facing)

Senior Full Stack Data Engineer (Client Facing)

Senior Full-Stack AI/ML Engineer (Production & MLOps)

At a Glance

We are using AI to accelerate due diligence and deepen insights for Private Equity funds. We are hiring a full stack engineer who is comfortable contributing to all layers of the application and developing features end to end.

  • Location: London, UK (Hybrid, In-person 4 days per week)
  • ExperienceRequired: +5 years
  • Remuneration: £65k → £100k + Generous ESOP
  • Visa: Unfortunately, we don’t sponsor visas yet. You must have the right to work in the UK.


About Capsa AI

Empowering Private Equity with Advanced AI – Capsa AI is an operating system that aggregates, structures, and generates insights from company and market data.


Our AI solutions reduce time spent on mechanical tasks and increase returns by analysing vast amounts of data to provide clear, actionable insights. Our vision is to become the leading AI platform for private capital funds, transforming how private investments are analysed and managed.


Our Team and Progress

Our founding team has deep domain expertise in Private Equity and AI. Our CEO, Danyal, has over 6 years of experience in Private Equity and Investment Banking at blue-chip financial institutions such as AEA Investors, Citigroup, and Deutsche Bank. Our CTO, Callum, has over 6 years of experience in Machine Learning and AI, having worked at leading defense companies like QinetiQ and retail tech startups such as Standard AI. The entire team are early stage startup veterans, with a passion for building great products.


Just one year after our December 2023 founding, we are already generating revenue, serving top-tier PE funds managing over £30 billion across the US, UK, and Germany. Furthermore, we’ve raised over £1.8 million in funding from prominent fintech venture capitalists and private equity angels, underscoring the confidence of industry leaders in our vision and potential.


Our Philosophy

  • Small team: Small talented teams outperform large and slow-moving companies. We avoid bureaucracy, keep meetings to a minimum and focus on creating value.
  • Simple where possible:We are passionate about new technology (in particular Machine Learning and AI), but we are more passionate about solving problems for our customers. We strive to find the best solution, be it cutting-edge or old-school.
  • Customer obsessed:We take every opportunity to talk to our customers. We obsess over their problems and work every day to make them happy.


About the Role

We are looking for a full stack engineer who wants to help shape the future of private equity and our company. As an early stage engineer you will:

  • Work directly with our founding team.
  • Help design our application architecture.
  • Ship features that our users care about, wherever they are in the stack.
  • Participate in strategy and product ideation sessions, influencing our product roadmap.

Working at Capsa AI will be hard work, it will be messy and at times it will be stressful. However, you will:

  • Experience the process of taking the company from 0.5 to 1.
  • Shape the company's vision and will have a direct impact on its success.
  • Have the opportunity for fast career growth.
  • Have the opportunity to participate in the upside of an ultra-growth venture.
  • Have fun


Apply if:

  • You have experience with our stack: Python, FastAPI, Postgres, SQLAlchemy, Alembic, Typescript, React, LlamaIndex / LangChain, PyTorch, HuggingFace, OpenAI, Docker, Azure, 
  • You have taken entire products or features from ideation to deployment and you’ve measured their impact.
  • You enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer.
  • You thrive in a fast paced environment.
  • You like to take ownership and work independently.
  • You are excited about joining an early-stage venture.


Don’t apply if:

  • You want to work on a single layer of the application.
  • You prefer to work on well-defined problems.
  • You need clear, pre-defined processes.
  • You prefer a low-pressure environment.


Additional Perks

  • Private healthcare insurance. 
  • One month per year remote working.
  • Budget for setting up your Home-Office.


Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.