A hands-on seat on a growing engineering team, building and shipping features across React and TypeScript, Node.js, PostgreSQL and AWS. You will also work on the AI-powered workflows running through the product, and you will own what you build from first commit through to production.
It suits someone who likes working across the whole stack rather than settling into one end of it.
What you'll do
- Own full-stack feature delivery across React and TypeScript, Node.js on Lambda, and PostgreSQL
- Build agentic AI workflows: tool-calling pipelines, LLM-integrated automation and AI-assisted experiences
- Build event-driven, serverless backends on AWS Lambda
- Reach for serverless containers when a workload is too heavy to run any other way
- Write infrastructure as code in SST, Pulumi, Terraform or CDK
- Contribute to the architecture decisions on data modelling, API contracts and asynchronous processing
- Build applications that stay reliable and maintainable, with production readiness taken seriously
- Work with engineers and stakeholders to understand the requirement before building the solution
- Contribute to observability and operational quality across the systems you build
What we're looking for
- 5 to 8 years of software engineering experience
- 3+ years hands-on with TypeScript, React and Node.js
- Strong React fundamentals: component composition, state management and performance
- Experience building and running serverless or event-driven backends on AWS Lambda
- Hands-on PostgreSQL, including schema design, query optimisation and migrations
- Comfortable writing infrastructure as code in SST, Pulumi, Terraform or CDK
- Some exposure to LLM APIs or agentic frameworks, and real curiosity to go further
- Solid software engineering fundamentals and comfort in production environments
- Clear written and verbal communication
Experience in SaaS, logistics, supply chain or freight technology is a strong plus.
Who tends to do well here
Engineers who see things through from idea to delivery and stay hands-on across the stack. Who enjoy a difficult problem, are curious about where AI tooling is going, and care about writing code that is still clean when someone else opens it next year.