Job Title

Overview This AI Engineer role at Culture Amp is based in Sydney, NSW, AU. Role seniority is mid level. About Culture Amp Culture Amp is the worlds leading employee experience platform, empowering companies of all sizes and industries to transform employee engagement, drive performance management, and develop highperforming teams. It serves more than 6,500 organisations worldwide. Why Were Looking We are building an AI Coach that integrates survey insights, performance management and interpersonal dynamics to deliver personalised support at scale. You will work at the intersection of applied AI research and product engineering, converting research into production systems that solve real customer problems. What You''ll Do Stay up to date with current research, literature and provider offerings. Design, implement and evaluate features of our multiagentic platform and systems using modern frameworks (e.g., LangGraph) for stateful, multiturn coaching conversations. Advise, help build and orchestrate data pipelines that unify fragmented workplace data (surveys, goals, performance reviews, feedback, 11 notes) into coherent coaching context. Translate customer requirements into technical solutions, working backwards from user needs to system design, and create technical documentation to support literacy, technical transfer and engineering practice. Partner closely with product, design and people science to ensure the developed features are fit for purpose and aligned with existing product expectations. Contribute to evaluation frameworks and bias testing to meet enterprise requirements for transparency and fairness. Build working prototypes integrated into our environments that validate new approaches and accelerate learning. What We''re Looking For Must Haves Proven commercial experience taking ML/AI systems to production. Strong technical writing and communication skills. Full stack software development experience, preferably in Python, React and PGVector. Strong software engineering fundamentals: clean, tested and maintainable code. Experience leveraging AI tooling for software development. Experience with LLM application development (prompt and context engineering, RAG, agent architectures). Values alignment: proactive, risktaking, humility and pride in work quality, stability, extendability and maintainability. Desirable Handson experience designing and integrating data pipelines within rigorous security standards. Pragmatic, solutionfocused mindset evaluating technology for scalable problem solving. Strong Signals Experience at startups or founding teams, comfortable with ambiguity and fast iteration. Postgraduate degree (Masters or PhD) in Machine Learning, Computer Science, Applied Mathematics or a related field. Evidenced ability to take cuttingedge techniques from paper to production. Experience with evaluation/benchmarking frameworks for AI systems. Experience integrating scalable solutions such as advanced SpeechtoText (STT) and TexttoSpeech (TTS) pipelines (Whisper, ElevenLabs) with streaming capabilities. Experience implementing GraphRAG or Knowledge Graphs (Neo4j). Bonus Familiarity with people analytics, HR tech or behavioural science applications. Contributions to data ethics, algorithmic fairness or responsible AI initiatives. Opensource contributions or public technical writing. Benefits Employee Share Options Program. Programs, coaching and budgets to support personal and professional growth. Access to external providers for mental wellbeing and coaching support. Monthly Camper Life Allowance. Team budgets dedicated to teambuilding activities. Quarterly wellbeing pauses. Extended yearend breaks. Excellent parental leave and inwork support programmes. Five social impact days a year. MacBooks and a homeoffice budget. Medical insurance coverage for employees and families (available in the US and UK). EEO and Inclusion Culture Amp is committed to diversity, equity and inclusion, with Employee Resource Groups and ally communities. We have a strong commitment to antiracism and aim to lead by example. We encourage applicants from underrepresented backgrounds and provide voluntary diversity questions which are optional and confidential. #J-18808-Ljbffr