Software Engineer (Data & AI)

Matching is the core engine behind our marketplace. It determines which of our 4 million participants get surfaced to researchers - and whether a research study succeeds or fails.

We’re hiring an engineer to own this system end to end. From core backend architecture to ranking logic and AI enhancements, you’ll continuously improve a system that directly impacts customer experience and business outcomes

Respondent is building the infrastructure that powers participant recruiting for the research industry. Our mission is simple but ambitious: to make it effortless for researchers to find high-quality human participants - whether they’re testing a product, exploring a market, or validating an idea.

From our founder’s first recruits on a NYC subway to a global panel of 4 million participants across 150+ countries, we now support research for companies like Stripe, Microsoft, and Canva. Our panel is one of the most diverse and responsive in the industry.

We’re a 30 person team across Sydney, Manila, and the US. We’re intentional about collaborating in person - serendipitous hallway conversations, whiteboarding sessions, and quick alignment cycles help us move faster and build something great together.

We’ve gone from 0 to 1, recently reaching profitability and intending to stay so. We’re scaling with intention and reinvesting in the business to grow our platform, panel, and team. Joining at this stage means your work will have a direct impact as we take Respondent from 1 to 10.

The role:

Matching sits at the heart of Respondent - it determines how researchers discover the right profiles, and ultimately whether research studies are completed successfully.

You’ll be joining our Sydney team as a Senior Backend Engineer working closely with Product and Engineering to own and evolve this core system.

Day to day, you’ll design and refine our core matching engine, including our search (semantic and traditional) and ranking algorithms, across millions of profiles. You’ll work across large datasets, apply AI thoughtfully where it adds real value, and partner closely with Product to define clear success metrics and move them. This is commercially grounded work - shipping improvements quickly, measuring impact, and iterating.

This role suits someone who thrives on. You’re comfortable operating with ambiguity, making pragmatic decisions, and steadily raising the bar on a system that is the heart of our product.

What You’ll Do

• Own and evolve our matching engine: Design and improve the systems that connect researchers with the right participants - improving relevance, speed, and quality across our marketplace
• Build high-performance backend systems: Architect APIs and services that operate over large datasets with low latency and high reliability.
• Design ranking and retrieval logic: Improve search, filtering, scoring, and ordering using structured rules, heuristics, and AI-driven approaches where appropriate.
• Apply AI pragmatically: Experiment with embeddings, semantic search, predictive scoring, or LLM-assisted workflows - crafting product-ready solutions.
• Define and measure matching quality: Work with Product to define success metrics (e.g., conversion, response rates, precision/recall) and continuously improve them.
• Make smart architectural trade-offs: Balance explainability, performance, scalability, and complexity in a fast-moving startup environment.

What You’ll Bring

• Strong backend foundations (Typescript first): Deep experience building scalable services and APIs. Comfortable with large datasets, optimizing queries, and reasoning about performance. Our stack includes TypeScript, Node.js, AWS and MongoDB - but we care more about your ability to ship than a perfect tech match.
• Experience with search, ranking, or matching systems: You’ve worked on problems involving recommendation engines, ranking systems, semantic search, or large-scale filtering - even if not formally called “matching.”
• Applied AI/ML exposure: You understand embeddings, vector search, or predictive modelling in practice - and ideally have shipped ML-powered features to production
• Builder mindset: You’ve built or re-architected a core system in a fast-moving startup or similarly ambiguous environment. You move quickly and turn messy problems into working systems.
• High ownership: You’re comfortable taking full responsibility for a critical system - defining problems, designing solutions, shipping, measuring, and iterating without heavy process.
• Real impact: You’ll be part of a small, high-ownership engineering team where your work ships fast and directly shapes the experience for customers like Stripe and Canva.
• Profitable and growing: You’ll get the excitement of startup growth with the stability of proven traction and profitability.
• Modern tech and mindset: You’ll work with the latest tools and AI-powered dev practices, giving you a front-row seat to cutting-edge engineering.
• Culture that cares: You’ll join a tight-knit global team (Sydney, Manila, US). We’re collaborative, supportive, and believe in balancing high performance with a fun workplace.