Senior AI Engineer (AI Engineering)

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

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

2. Take-home task

3. Technical interview based on the task

4. Interview with Product Manager

5. Final interview with Hiring Manager