Lendable

fintech

SeniorAIEngineer(Contract)

London, United Kingdom CONTRACT Remote Friendly
The Brief

“Senior AI Engineer (Contract) at Lendable. Skills: AI Engineering, LLM development, Full-stack development, API integrations, Automation. Build AI integrations and data sources. Create connectors and integrations for company data (Google Workspace, Slack, Jira, GitHub, Snowflake, Confluence)”

What You'll Achieve.

Make the whole company more efficient; Supercharge internal teams; Remove friction; Automate the tedious; Give colleagues back time to focus on high-value work; See the direct impact of what you build; Ship an integration and watch it save hours of manual work; Build a tool and see a team adopt it the same week; Make a tangible difference; Deliver measurable impact; Save time; Reduce errors; Increase adoption

Industry & Context.

fintech
Problems you'll solve

Solve problems; Remove friction; Automate the tedious; Give colleagues back time to focus on high-value work; Solving real problems

What They're Looking For.

Must Have

4+ years of software engineering experience, full-stack skills in Python or TypeScript, Experience shipping containerised software to Kubernetes, Proven experience building AI tooling used by others in a commercial environment, 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 workflow automation tools (n8n, Zapier, Make or similar), Familiarity with vector databases (Pinecone, Weaviate, pgvector), Experience with AWS Bedrock or other LLM provider APIs, Experience of building and rolling out MCPs, Experience of building and rolling out AI, Frontend skills with Next.js or React for internal tooling

What You'll Do.

Build AI integrations and data sources

Create connectors and integrations for company data (Google Workspace

Build and maintain knowledge base pipelines

MCP integrations and API connections

Work with security and data governance requirements

Support internal teams to create their own AI-powered data sources

automated workflows and internal tools

guardrails and building blocks for non-engineers

Contribute to internal automation platform using AWS Bedrock

n8n and custom-built solutions

Identify high-leverage opportunities

measure outcomes and iterate

Stay curious about emerging tools and techniques and apply them

How You'll Work.

Team & Collaboration

Work closely with the PM and engineering lead; Support internal teams to create their own AI-powered data sources, automated workflows and internal tools; Work in small teams of exceptional people

Process & Methodology

Take ownership end-to-end — from understanding the problem, through design and implementation, to monitoring and iteration, Own work from 'what should we build?' through to 'is it still delivering value?'

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