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Join Deputy's AI Scheduling team and work on one of the most used parts of our product. Businesses have created more than a billion shifts with Deputy, and Scheduling is where business demand, employee availability, labour costs and compliance meet. The team is bringing AI and automation into the decisions managers make every day, helping them build compliant, cost-effective schedules at scale.
It's a mature, business-critical product with plenty left to build. You'll help modernise established workflows, make it faster for larger customers and find where AI can make scheduling simpler.
This is a hands-on senior engineering role with no direct reports. You'll spend most of your time designing, building and shipping with the other engineers in the squad, owning meaningful projects and looking for the next problem worth solving.
Lead the technical design of squad projects, build and ship them, and stay with them once customers depend on them.
Ship in small, well-tested steps, improve the code you touch, and raise risks early so there are no late surprises.
Work with Product, Design and Data to turn customer problems into features that make a measurable difference.
Develop a deep understanding of the Scheduling product and its architecture, so you can help the team make sound technical decisions.
Make pragmatic trade-offs between shipping quickly and keeping Scheduling fast, dependable and ready for enterprise scale, with an eye on what the product will need next.
Improve the performance, reliability, security and maintainability of a multi-tenant product used by businesses around the world.
Use design reviews, lessons from incidents and small proofs of concept to back your decisions with evidence.
Set a high bar in code reviews, with feedback that helps other engineers grow.
Mentor engineers in the squad and help build a team where people challenge ideas and learn from mistakes.
Use AI-assisted and agentic development tools on real work, and form your own view of where they help and where they do not.
Help the team build good practices for reviewing, testing, monitoring and documenting machine-drafted code, so what ships is correct, secure and understood by its owners.
When you build customer-facing AI features, plan for evaluation, guardrails, cost, latency and graceful failure from the start.
4+ years of experience as a backend software engineer, including taking features from design through to production.
Experience running customer-facing software and making trade-offs between delivery speed, reliability and long-term maintainability.
Experience designing APIs (REST or RPC) and building services with good monitoring and observability.
You have led or shaped technical designs, and you can explain engineering decisions to technical and non-technical people.
You have worked with Product and Design on problems that were not fully defined, and found practical ways to move them forward.
You already use AI coding tools in your own work, and you review their output as critically as a colleague's code.
Building and operating distributed, cloud-native or multi-tenant SaaS systems at scale.
Designing for resilience across services, event-driven systems and large relational or NoSQL data stores.
Shipping LLM-backed or agentic features in production.
Working on workforce management, scheduling or another operationally complex product.
PHP or Go in production, and tools like protobuf, gRPC, MySQL, Redis, DynamoDB, SQS and Elasticsearch.