at Relevance AI · 51-100 employees
Relevance AI provides a tool- and model-agnostic platform to build, train, and deploy vector-powered, multi-agent AI systems that integrate with existing tech stacks to automate end-to-end workflows.
Location 📍: Sydney, AU, Hybrid (3 days in office required) About Us 🚀 At Relevance AI, we’re building the home of the AI workforce. Our mission is simple: empower every team to delegate meaningful work to AI agents that think, act, and collaborate like experts. With Relevance AI, anyone can create and manage intelligent agents that handle workflows, decisions, and collaboration - all within one unified platform. Our technology already powers industry leaders such as Canva, Databricks, Confluent, Autodesk, Lightspeed, Rakuten, Aveva, Qualified, and Activision Blizzard, helping them scale excellence across operations, marketing, and sales. We’re backed by Bessemer Venture Partners, Insight Partners, Peak XV, and King River Capital, and raised our Series B in April 2025 to accelerate growth and push the boundaries of agentic automation. Headquartered in San Francisco and Sydney, we operate on a hybrid model and thrive on curiosity, collaboration, and execution - we move fast, think big, and win together. In 2025, we were proud to be named LinkedIn’s #1 Startup in Australia. If you want to define how the world works with AI, join us. The Role 🥳 The greatest engineers today aren't just writing code faster—they're spending more time solving problems and building products that couldn't have existed a year ago. Our team works at the frontier of AI-native development where curiosity, product thinking, rapid experimentation and judgement are embedded in our ways of working. As an Engineering Manager, you'll lead a team of engineers working on some of the hardest problems in AI—helping shape how AI agents are built, orchestrated, and operated in production on our Enterprise platform. You'll report to our Head of Engineering and partner closely with customer-facing teams and founders while staying close enough to the technical work to guide execution, raise the bar on quality, unblock your team and develop AI-native engineers. Your mission? Lead a high-performing AI-native engineering team to drive strong technical outcomes, and help deliver ambitious roadmap goals in a fast-moving environment. How We Build ⚒️ We believe that AI is fundamentally changing software and what it means to be an engineer. That means our team works differently: - AI engineering (coding agents, loops, eval) is a core part of every engineer's workflow. - Engineers own product areas and customer problems end-to-end, not just implementation. - We prototype quickly, validate with customers, and iterate relentlessly. - We ship continuously, often multiple times a day. - We care about product impact as much as technical quality. If you enjoy experimenting with frontier models, trying new tools, and constantly improving how you build software, you'll fit right in. Meet The Team 👋 - Paulwyn, Head of Engineering https://www.linkedin.com/pulse/relevance-ai-conversation-meet-our-head-engineering-paulwyn-esnvc/ - Peter, Engineering Manager https://www.linkedin.com/pulse/meet-peter-engineering-manager-relevance-ai-relevanceai-kxrgc/ Your impact💥 - Lead and develop a team of 4 - 8 AI-native engineers, creating clarity and supporting performance, coaching, and execution in a high-trust environment. - Elevate product thinking within your team so we build the right thing, tied to customer outcomes, not just tickets closed. You push the team from output to outcomes. - Set the standard for AI-native engineering practices; coaching engineers on agentic workflows, context engineering, and eval discipline. - Demonstrate technical credibility and contribute meaningfully in the codebase, joining design reviews, reviewing code, fixing bugs, and shipping small features. - Own quality and reliability; on-call health, running honest postmortems, closing the build-and-run loop. - Handle tough conversations with empathy and conviction, including feedback, alignment challenges, and expectation setting. - Hire bar-raising candidates by partnering closely with Talent Acquisition to execute hiring plans and close strong engineers. Who We’re Looking For 🧠 In one-line: a hands-on AI-native engineering manager who cares deeply about customer outcomes, brings strong product thinking and enjoys leading small fast-moving AI teams. You'll likely thrive here if you demonstrate: - AI-Native Building: You are hands-on and fluent in what is possible with coding agents — using AI daily to build context, decompose problems, orchestrating build, reviewing quality and can show that you’ve shipped non-trivial work in practice. - Product Thinking & Judgement: You think like a product owner and reason from customer outcomes. You care about building the right thing, understand who uses what your team ships, why it matters to the business and make tough calls on what to kill. - People Leadership: Track record of managing high performing engineering teams of comparable scope (4-8 engineers) in problem-dense environments. - Technical Credibility: You bring technical depth in backend, APIs, distributed systems and stay meaningfully hands-on in the codebase, ship things, contribute to design reviews and technical decision-making. - Hiring Excellence: You are a talent magnet and have personally closed strong engineers. You know what it means to hire great AI-native engineers. - Belief in our mission. You raise the standard for people around you, you're comfortable with ambiguity and pace, and you believe a smaller AI-native team can out-build a larger, traditional one. Our Tech Stack (so far) 💻 Experience in our exact stack is not required — what matters more is how fast you can pick up a new one, and how deeply you already use AI coding agents as part of your daily workflow. - Frontend: React, Vue.js, Typescript - Backend: Express.js, Node.js, Typescript, Python - Database: PostgreSQL, MongoDB - Cloud Infrastructure: AWS, Vercel, Terraform, Kubernetes - AI Coding Tools: Claude Code, Curs