Senior AI Platform Engineer in London

Senior AI Platform Engineer in London

London Full-Time 80000 - 98000 £ / year (est.) Home office (partial)
United States Digital Space LLC

At a Glance

  • Tasks: Design and build the next-gen AI platform for innovative applications.
  • Company: Join a leading AI platform transforming global debt markets.
  • Benefits: Competitive salary, equity, flexible working, and generous holiday allowance.
  • Other info: Collaborative culture with opportunities for growth and innovation.
  • Why this job: Shape the future of AI while making a real impact in finance.
  • Qualifications: 5+ years in software engineering with AI/ML experience.

The predicted salary is between 80000 - 98000 £ per year.

About the company the company is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion.

Debt markets are vast, global, and mission‑critical, yet still run on fragmented data, PDFs, and manual workflows. the company replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high‑value workflows across global markets.

Today, the company powers teams at 300+ blue‑chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors.

The business is scaling at exceptional speed, with rapid expansion in the US and best‑in‑class retention driven by deep workflow adoption.

We’re at a defining inflection point.

With proven product‑market fit and strong, global market pull, the company is accelerating toward becoming the category‑defining platform for debt markets worldwide.

The Opportunity

The AI Engineering team at the company is building the next generation of AI capabilities that will power our products for years to come.

We're looking for a Senior AI Platform Engineer to help design, build, and evolve the core AI platform that enables Generative AI, Agentic AI, and machine learning applications across the business.

This is an opportunity to join at the beginning of the platform's journey.

Rather than inheriting a mature internal platform, you'll help shape its architecture, define engineering standards, and build reusable infrastructure that allows AI teams to move quickly, safely, and at scale.

Working alongside backend engineers and AI engineers, you'll create the shared platform services that power everything from intelligent document understanding to autonomous AI agents capable of running scheduled workflows, generating morning briefings, identifying distressed companies, and supporting future AI‑powered product experiences.

  • Every day is different, but here's an example of the kind of things you'll work on:
  • Design, build and continuously evolve the enterprise AI platform that powers AI products across the company.
  • Develop scalable AI services supporting Agentic AI, Retrieval‑Augmented Generation (RAG), embeddings, vector search, model serving, and intelligent automation.
  • Build orchestration layers that transform structured and unstructured enterprise data into reusable AI capabilities.
  • Develop production‑ready AI applications using modern LLM frameworks and orchestration tools.
  • Design reusable platform components for prompt management, model serving, vector search, embeddings, AI gateways, and evaluation services.
  • Build APIs, SDKs, and developer tooling that enable self‑service AI development across engineering teams.
  • Design secure, scalable deployment pipelines for AI models and applications.
  • Build AI observability capabilities including monitoring, tracing, evaluation, cost optimisation, and production quality measurement.
  • Collaborate closely with AI Engineers, Backend Engineers and Engineering Leadership to define platform architecture and engineering standards.
  • Establish engineering best practices around testing, governance, Responsible AI, deployment, and operational excellence.
  • Continuously evaluate emerging AI technologies and evolve the platform as the ecosystem rapidly advances.
  • What Makes This Role Different

Unlike many AI Platform roles that focus on maintaining existing infrastructure, this role is centred around building the platform from the ground up.

You'll join at an early stage where many architectural decisions have yet to be made, giving you genuine influence over how AI is built, deployed, and operated across the company.

Within your first six months, you'll help build the platform that powers production AI agents capable of running autonomously in the background—supporting workflows such as scheduled market briefings, distressed company discovery, and future intelligent financial research products.

Rather than owning a single AI product, you'll build the shared capabilities that enable multiple engineering teams to rapidly develop, deploy, and operate AI solutions at scale.

You'll be one of a small number of senior engineers helping shape the technical direction of the platform alongside the Engineering Lead and fellow senior engineers.

About You

  • AI Platform Engineering
  • 5+ years of software engineering experience, including 2+ years building AI/ML platforms, Generative AI applications, or production machine learning systems.
  • Experience designing and deploying enterprise AI applications into production with a strong focus on scalability, reliability, and developer experience.
  • LLMs & Agentic AI
  • Hands‑on experience building applications powered by Large Language Models (LLMs).
  • Experience building Model Context Protocol (MCP) and Retrieval‑Augmented Generation (RAG) solutions, making use of embeddings, vector databases, and modern LLM orchestration frameworks.
  • Experience building or contributing to agentic AI systems, intelligent workflows, or orchestration frameworks.
  • Backend & Platform Engineering
  • Strong backend engineer with production experience using Python and/or Type Script.
  • Designed scalable backend services, REST APIs, and event‑driven architectures.
  • Experience building reusable platform capabilities, internal developer tooling, SDKs, or shared engineering services.
  • Cloud & Infrastructure
  • Strong experience building cloud‑native applications.
  • Comfortable working with Docker, Kubernetes, CI/CD pipelines, and containerised deployments.
  • Experience with solutions such as AWS Bedrock and Agent Core.
  • Understand how to deploy, monitor, and operate AI services in production.
  • AI Operations & Observability
  • Experience implementing monitoring, tracing, evaluation, and cost optimisation for AI systems.
  • Experience with observability solutions such as Arize Phoenix, Langfuse, or Langsmith.
  • Understand the operational challenges of deploying LLM‑powered applications, including latency, reliability, hallucination monitoring, and model quality evaluation.
  • Collaboration & Technical Leadership
  • Enjoy collaborating across multiple engineering disciplines to shape technical direction and establish engineering best practices.
  • Comfortable operating as one of a small number of senior engineers, influencing architecture and platform direction without necessarily having formal management responsibilities.
  • Thrive in fast‑moving environments where many platform capabilities are still being designed and built.
  • Bonus Points

Experience with any of the following would be highly advantageous

  • AI gateways and model routing
  • Prompt management platforms
  • AI evaluation frameworks
  • Lang Graph, Lang Chain, Llama Index, DSPy, Crew AI or similar orchestration frameworks
  • Vector databases and semantic retrieval
  • Knowledge graphs or document understanding systems
  • Building internal AI platforms used by multiple engineering teams

Benefits

We’re a scaling start up, and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people.

We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel.

  • Financial & Insurance
  • Competitive Salary (our salary bands are benchmarked at the top end of the market)
  • Equity
  • Pension (your minimum contributions are 4% with the company matching up to 7%)
  • Private Medical Insurance
  • Paid sick leave with Income Protection for long periods of illness
  • Group Life Assurance
  • Season Ticket Loan & Cycle to Work schemes
  • Time off
  • 25 holiday days per year
  • Local public holidays (with the ability to exchange them for alternative days)
  • Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work
  • Work abroad for up to 3 months a year
  • 1 month paid sabbatical after 5 years of service
  • Enhanced parental leave & flexible working arrangements available
  • Training & Culture
  • Professional learning and development budget
  • AI experimentation budget of £800 (UK) per employee to trial AI tools
  • Quarterly team socials
  • Summer and Winter company social events the company is an equal opportunities employer

At the company we are dedicated to building and promoting a fair and inclusive workplace where everyone can reach their full potential and truly belong.

We recognize that building diverse teams enables a more creative and productive environment.

If you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway.

You might just be who we’re looking for — either for this role, or perhaps another.

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United States Digital Space LLC

Contact Details:

United States Digital Space LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior AI Platform Engineer in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at United States Digital Space LLC or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

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We think you need these skills to ace Senior AI Platform Engineer in London

Software Engineering
AI/ML Platform Development
Generative AI Applications
Large Language Models (LLMs)
Model Context Protocol (MCP)
Retrieval-Augmented Generation (RAG)
Python

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at United States Digital Space LLC.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at United States Digital Space LLC and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at United States Digital Space LLC

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If United States Digital Space LLC uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.