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Cornspring is an innovative FinTech startup with a mission to empower Family Offices and Asset Owners with real-time, AI-driven data intelligence and portfolio insights.

We are tackling one of the most complex and valuable challenges in finance. Our clients operate at the highest levels of global markets, managing billions in assets, yet they remain constrained by legacy systems that are slow, fragmented, and outdated.

Cornspring is redefining Family Office services by applying state-of-the-art generative AI and Large Language Models to investment, accounting, and operational data. Our platform delivers faster insights, greater transparency, and entirely new ways of interacting with financial information.

The role

We are looking for an exceptional Senior Software Engineer with a strong ML and LLM focus, and the ability to build production-grade AI systems end-to-end.

This is a pivotal role in which you will shape core system architecture, design and deploy AI-driven features, and work hands-on across backend systems and applied LLM development. You will have real ownership over technical decisions and a direct impact on mission-critical products used by sophisticated financial clients.

If you enjoy building scalable systems, deploying LLMs in real production environments, and working in a high-calibre engineering culture, we would love to speak with you.

Key Responsibilities

Backend Engineering & Architecture

Design, build, and optimise scalable backend systems in Azure, utilising Python, containers, FastAPI, and modern architectural approaches
Take complete ownership of services throughout their lifecycle: from initial concept and design through to deployment, monitoring, and ongoing iteration
Enhance performance and reliability through refactoring, algorithmic improvements, asynchronous processing, and strategic caching
Work at pace by prototyping rapidly, evaluating outcomes, scaling up successful approaches, and quickly adapting or pivoting when necessary
Collaborate closely with product and data teams to transform intricate financial and AI requirements into robust, production-ready features

ML, AI & LLM Systems

Design and implement LLM-powered features using both SaaS models and locally hosted models
Build and evolve Retrieval-Augmented Generation (RAG) pipelines for both structured and unstructured financial and accounting data
Leverage HuggingFace, vLLM, prompt engineering, and model orchestration frameworks to deliver advanced AI solutions
Implement robust evaluation, testing, and monitoring processes for LLM outputs, prioritising correctness, determinism, latency, and cost efficiency
Optimise model selection, inference strategies, and prompting techniques to ensure reliable performance within real-world production constraints
Contribute to the development of internal AI tooling and workflows, driving measurable improvements in developer productivity and overall product quality

Technical Leadership & Collaboration

Contribute to engineering best practices and play an active role in shaping technical standards and architectural decisions
Work in close collaboration with engineering, product, and data teams to deliver secure, scalable, and well-designed solutions
Mentor fellow engineers by conducting code reviews, engaging in technical discussions, and providing practical examples

Quality, Reliability & Continuous Improvement

Champion lean and clean architecture to ensure maintainable code and uphold rigorous testing discipline
Drive ongoing improvements in system performance, scalability, and the overall developer experience

Requirements

Degree in Computer Science (or equivalent), with strong software engineering fundamentals
Significant hands-on experience as a software engineer, including senior-level ownership and decision-making
Strong experience building AI-driven systems, with particular depth in LLMs and applied ML (e.g. RAG, prompt engineering, model evaluation)
Excellent Python skills and experience delivering production backend systems
Strong problem-solving, communication, and collaboration skills
A mindset oriented towards ownership, quality, and continuous learning

Benefits

Competitive salary and benefits, including private medical insurance, cash plan, life insurance, and income protection
Hybrid working: three days per week in our City of London office
An opportunity to work at the forefront of AI-driven finance, tackling genuinely complex and high-impact challenges
Hands-on exposure to advanced ML, LLM, and data technologies within real production systems
A collaborative, high-ownership startup environment offering exceptional learning opportunities
The chance to help shape the future of Family Office and Asset Management technology

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