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Engineering Manager, AI

Relevanceai
CompanyRelevanceai
CategoryEngineering
LocationSydney
RemoteHybrid
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted5 Aug 2026
Last verified6 Aug 2026
SourceEmployer ATS (ashby)
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Description
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. - Hir