About lizzyAI
lizzyAI is building the operating system for AI-supported recruiting, with structured interviews at its core. Our mission is to make hiring workflows structured, scalable, and insight-driven while keeping people in control of every consequential decision.
In less than two years, we have moved from early product development to enterprise traction with customers in Europe and the US.
Founded by German serial entrepreneur Yannis Niebelschütz, previously Founder & CEO of CoachHub, and backed by investors including NEA and Speedinvest, we are building the company and product for long-term category leadership.
About the role
You will help build the systems that keep recruiting work moving across candidate conversations, workflow coordination, and recruiter review. The work sits close to product: the infrastructure should be dependable, observable, and clear enough for people to understand what Lizzy is doing and what happens next.
You will own meaningful parts of that journey end to end, from the events that start a workflow to the evidence a recruiter reviews. You will work across product boundaries, make failure and recovery states explicit, and help a growing engineering team turn ambitious product behavior into systems customers can trust every day.
What you’ll do
You will combine hands-on delivery with system-level judgment. The role spans new product capabilities, the foundations behind them, and the operational details that make automated recruiting work safe and understandable.
- Build and operate backend services for candidate conversations, coordination, interviews, and structured evidence.
- Design APIs, events, and data models that connect recruiter and candidate surfaces while preserving important workflow state.
- Make asynchronous work observable through useful logs, metrics, traces, ownership, and clear recovery paths.
- Strengthen tenant isolation, permissions, privacy boundaries, and the handling of sensitive hiring information.
- Partner with product, design, and applied AI teammates to translate product intent into bounded, reviewable behavior.
- Ship in small, testable increments, review architecture pragmatically, and improve the engineering practices around the systems you own.
What you’ll bring
We value engineers who can move between implementation details and the human workflow the system supports. You do not need prior recruiting experience, but you should care about reliability, explainability, and the consequences of the software you ship.
- Strong experience building and operating production backend systems and APIs.
- Practical knowledge of data modeling, asynchronous workflows, queues, integrations, and service reliability.
- A thoughtful approach to security, privacy, tenancy, migrations, and operational ownership.
- The ability to investigate ambiguous failures and turn them into durable improvements rather than one-off fixes.
- Clear written and verbal communication, including the ability to make technical tradeoffs and risks visible.
- Interest in AI-assisted products where evidence remains reviewable and people retain control of consequential decisions.
- A high-ownership mindset, bias toward action, and comfort working in a fast-paced startup environment.
Your impact and growth
This is an opportunity to take meaningful technical ownership as the platform and team scale. Strong performance can grow into ownership of larger systems, architectural direction, and mentorship of new engineering teammates.
Why lizzyAI
- Help build a category-defining company at an early stage of enterprise growth.
- Work closely with founders, product, applied AI, and engineering on decisions that reach production quickly.
- Take real ownership and see the impact of your work from day one.
- Solve technically ambitious problems while protecting candidate care, customer trust, and human control.
