About the Role

You will be our first engineer in the US. Our engineering team is based in Sydney; our fastest-growing market is the US. We need a strong, hands-on engineer in the US timezone who can deliver product, support our customers, and be the foundation around which we grow the US engineering function. Our stack spans Go, Python, Node.js, React, and Vue, running on AWS with event-driven architecture.

Our platform is AI-powered: RAG pipelines, agentic workflows, LLM integrations, semantic search. You need to have built in this space.

You report to the Head of Engineering in Sydney. You will work alongside our dynamic US-based Head of Product, a Senior Product Designer, and a data allrounder. Together you own US product outcomes. You will be close to leadership and fast decision making.

We want you to be the technical anchor as the US team grows. If you have experience building teams, there is a path to leverage that. If your strength is deep technical contribution, we will add leadership around you. Either way, you will have shaped the US team from day one.

What We Expect

Build Product

• Own end-to-end delivery of US-priority features on the WorkOS platform. You decide the approach, make the trade-offs, and ship.
• Break ambiguous problems into increments that ship value early. Operate 0→1: architect new systems, build prototypes, iterate on real usage.
• Design and build AI-powered features — RAG, agentic workflows, LLM integrations, semantic search. This is the core of the product.
• Evaluate and integrate foundation models (OpenAI, Anthropic, open-source) with attention to cost, latency, and reliability.
• Understand the full lifecycle of ML-adjacent systems: data pipelines, embedding generation, retrieval infrastructure, evaluation frameworks. You don’t need to own these, but you need to be dangerous enough to triage, and know what questions to ask.

Improve How We Use AI to Build Software

• Bring strong experience in establishing standards for AI-assisted development: review criteria for AI-generated code, testing requirements, ownership accountability.
• Build a playbook for effective use of AI coding tools (Cursor, Copilot, Claude Code) across the engineering org.
• Instrument the impact — track code quality, review cycles, and delivery velocity so we know what’s working.
• Help drive this across both US and Sydney teams. Shared standards, not separate cultures.

Support US Customers

• Be the US-hours first responder for enterprise customer issues. Issues span application, infrastructure, and data — you triage across all three.
• Investigate, assess severity, and either resolve directly or hand off to Sydney with complete context.
• Build escalation playbooks and observability tooling that compress response times.
• This is transitional: as we hire dedicated data and infrastructure engineers you hand off domain-specific triage.

Partner with Product and GTM

• Be the engineering voice alongside the local Head of Product, designer, and data allrounder.
• Jump into customer calls, diagnose technical questions, translate customer pain into engineering priorities.
• Represent engineering in US-timezone decisions that can’t wait for Sydney.

Infrastructure

• AWS, Terraform, container orchestration (EKS, ECS), CI/CD.
• Contribute to observability, monitoring, alerting, and incident response.

Grow the Team

• Help hire and onboard the engineers and data professionals who will form the US team over the next 6–12 months.
• If you have team-building experience: shape the US engineering function — org design, hiring strategy, offshore/nearshore capacity.
• Work closely with the Head of Engineering in Sydney. One engineering org, not two.
• Raise the bar: code review, design feedback, mentoring, engineering fundamentals.

What You Need

• 6+ years of software engineering. Years matter less than what you’ve done with them.
• You’ve owned product outcomes end-to-end — decided what to build, not just written code.
• You’ve built AI/ML-powered features in production: RAG, agents, LLM integration, or similar.
• You’ve defined or significantly improved how an engineering team uses AI tools — not just your own workflow, but team-wide practices.
• Strong across application and infrastructure. Enough awareness of data systems to triage issues, ask the right questions, and hand off to specialists with useful context.
• Strong distributed systems fundamentals. You design for scale, resilience, and observability.
• Infrastructure experience: AWS, IaC, containers.
• Polyglot. Our stack is Go, Python, Node.js, React, Vue. You pick things up fast.
• Clear communicator. You can explain technical decisions to engineers, product partners, and customers.
• Comfortable with ambiguity, autonomy, and accountability. No safety net.
• Ideally experience as a founding or early engineer in a product company — comfortable with ambiguity and building from zero.

Why This Matters

Reejig is at a point of real inflection. We are building a company that will reshape how organisations operate in the AI era. The people who join now are not stepping into a role, they are stepping into a chance to build something with scale and long term impact. If you want work that changes your career and creates meaningful equity upside, this is the moment.