About the role
Operations is roughly half of Lendable's people. Central Ops Engineering is a small product engineering team that builds the tooling to help keep back office operations lean and efficient, while maintaining good customer outcomes.
We're hiring a senior product engineer who can own and deliver large problems in that space. You'll build the internal web apps and automations that agents use every day, and help shape how the team uses AI coding tools.
What you'll work on
Current problems include:
Complaints: we've already made handling much more efficient for officers, and are continuing to push on this.
Fraud and Fincrime: putting the signals an investigator needs into one place.
Quality assurance: using AI to review far more calls than a QA team can sample, and directing coaching to the agents who need it.
How we work
We use Claude Code, Codex, Augment and other AI tools every day. They've tripled our productivity, and we want you to help decide where we take that next. You'll hand real work to coding agents and take responsibility for what ships.
You'll work directly with ops agents and their managers, and with Product. Data Science and Analytics own the models and prompt engineering, and you'll build the tools that put their work in front of agents.
Who you are
An experienced product engineer with a strong track record of delivering practical, full-stack solutions on modern technology
Comfortable with ambiguity and focused on business outcomes, looking beyond the stated requirements to address the underlying problem
Experienced in shaping team ways of working and mentoring other engineers
Enthusiastic about AI-assisted development, ideally with a record of using it to improve how your team delivers
Our tech stack
This is what we use today, to give you a feel for the work. If your tech stack is different, we'd still like to hear from you: we've successfully onboarded engineers from different stacks in the past.
Backend: Python and FastAPI
Frontend: React, Next.js and Tailwind
Infrastructure: AWS, Docker, Kubernetes, Argo and Terraform
Data: SQL & Snowflake
Patterns: Domain Driven Design, message-driven systems and event sourcing
Interview process
Intro call with Talent (30 min).
Coding exercise in your own time ([2-3 hours max]). It's a small internal-tool problem, and you should use AI tools as you normally would.
Technical interview (60 min). You'll walk us through your exercise, then we'll change the requirements and extend it together.
Culture and behavioural interview (60 min), with time for your questions.
