Senior AI Engineer (AI Engineering)

Remote, USA
Posted Jun 13, 2026
Full-time

About Lendable

Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start:

One of the UK’s newest unicorns with a team of just over 700 people

Among the fastest-growing tech companies in the UK

Profitable since 2017

Backed by top investors including Balderton Capital and Goldman Sachs

Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)

So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days.

We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.

Join us if you want to

  1. Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1

    Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo

    Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

    We're looking for an AI Engineer to join our AI Engineering team at Lendable to help us enable developers to move faster whilst keeping quality high.

    Our mission is to bring all the lessons we have learned about AI development so far into one system so everyone can benefit. The system combines our Lendable Coding Agent - pronto, a system for measuring effectiveness of AI and the stability of our systems.

    This is a role where you'll be working with our engineers and product managers who build our products. You will improve the developer experience and improve our throughput. You’ll see instant impact with your work and participate in a highly collaborative environment.

    We need someone who takes full ownership — not just writing code, but thinking through the problem, designing the solution, shipping it, and making sure it keeps working. You'll own your work from "what should we build?" through to "is it still delivering value?".

    You'll also be working at the frontier of AI tooling — building with LLMs, experimenting with new approaches, and figuring out what's possible.

    What you'll be doing

    Build AI on top of our cloud closing agent pronto

    Create connectors and integrations that make company data available to AI systems (Google Workspace, Slack, Jira, GitHub, Snowflake, Confluence and more)

    Build and maintain knowledge base pipelines, MCP integrations and API connections that power AI tooling across the business

    Work with security and data governance requirements to ensure integrations are safe and appropriate

    Enable others to build with AI

    Support internal teams to create their own AI-powered data sources, automated workflows and internal tools using rapid app builder tools

    Build templates, guardrails and building blocks that make it easy for non-engineers to experiment safely

    Contribute to our internal automation platform using tools like AWS Bedrock, n8n and custom-built solutions

    Deliver measurable impact

    Work closely with the PM and engineering lead to identify the highest-leverage opportunities

    Ship quickly, measure outcomes (time saved, errors reduced, adoption) and iterate based on what you learn

    Stay curious about emerging tools and techniques — and apply them where they'll genuinely make a difference to our engineering output

  2. What we're looking for

    Essential

    4+ years of software engineering experience

    Proven experience building AI tooling used by others in a commercial environment

    Strong full-stack skills in Python or TypeScript

    Frontend skills with Next.js or React to build an interface for engineers

    Knowledge of MCP (Model Context Protocol)

    Experience shipping containerised software to Kubernetes

    Comfortable working with LLMs, embeddings and AI application patterns

    Experience designing and building API integrations

    Self-starter who takes ownership end-to-end — from understanding the problem, through design and implementation, to monitoring and iteration

    Motivated by impact — you want to see your work used and making a difference

    Nice to have

    Experience with AWS Bedrock or other LLM provider APIs

    Experience with monitoring tools such as Datadog

    Experience with creating guardrails for products: SLOs, DORA metrics

    How you'll work

    You’ll be part of a small core team that works with engineering representatives from across the company. We have a vision of how we can accelerate the engineering process with AI and you’ll be working with this group to complete the plan. We will also experiment and adapt the plan as new AI tooling and approaches emerge.

    We value shipping and learning over perfection. The goal is always to deliver something useful, learn from how it's used, and improve. You won't be directly client-facing, but your work will directly impact colleagues across the business — and you'll hear about it when something you built makes their day easier.

    Why join?

    See your work make a difference This isn't a team where your code disappears into a monolith. You'll build something on Monday and see it saving someone time by Friday. Every integration and tool you ship has a direct line to engineering efficiency.

    High leverage A small core team means your contributions have outsized impact. No layers, fast decisions, real ownership.

    Build new things We're building a platform from the ground up, not maintaining legacy systems. You'll shape how AI gets used across Lendable.

    Work at the frontier AI tooling is moving fast. You'll work with the latest in agentic AI, workflow orchestration and LLM tooling — applied to real problems, not just proof-of-concepts.

    Interview process

    1. Screening call with Hiring Manager

      Take-home task

      Technical interview based on the task

      Interview with Product Manager

      Final interview with Hiring Manager

      Life at Lendable

      • The opportunity to scale up one of the world’s most successful fintech companies.

        Best-in-class compensation, including equity.

        You can work from home every Monday and Friday if you wish - on the other days, those based in the UK come together IRL at our Shoreditch office in London to be together, build and exchange ideas.

        Enjoy a fully stocked kitchen with everything you need to whip up breakfast, lunch, snacks, and drinks in the office every Tuesday-Thursday.

        We care for our Lendies’ well-being both physically and mentally, so we offer coverage when it comes to private health insurance

        We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London

        Check out our blog!

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