Senior Applied AI Engineer
Culture Amp7 hours ago
Sydney, AustraliaSenior
Responsibilities
- Design, implement, and evaluate agentic AI capabilities and stateful multi-turn systems using frameworks such as LangGraph.
- Build and orchestrate data pipelines and integrations that create coherent context from workplace data.
- Develop persistent user memory, context graphs, custom ontologies, relational and procedural memory, and user preferences.
- Build and evaluate RAG systems, including preprocessing, hybrid search, and graph-based agentic frameworks.
- Own prompt engineering, scalable evaluation, LLM-powered analysis, and continuous system improvement.
- Translate customer requirements into technical designs and documentation for product teams.
- Partner with product, design, and people science teams to deliver scalable features.
- Develop evaluation frameworks and bias testing for transparency, fairness, and responsible AI.
- Create and monitor production guardrails and safety systems.
- Track AI research and provider offerings and apply relevant techniques in production.
Requirements
- Proven commercial experience taking ML or AI systems to production.
- Hands-on experience with knowledge graphs and graph databases such as Neo4j or Neptune.
- Experience with production LLM evaluation and observability, including LLM-as-judge, evaluation datasets, human-in-the-loop labeling, threshold scoring, tracing, and monitoring.
- Experience designing and scaling production multi-agent systems, including orchestration, prompt and context engineering, RAG, memory, and agent architectures.
- Full-stack software development experience, ideally with Python, React, and PGVector.
- Strong software engineering fundamentals and experience writing clean, tested, and maintainable code.
- Ability to instruct and delegate complex workflows to autonomous agents and build feedback loops for reliable operation.
- Hands-on experience designing and integrating data pipelines across systems and handling messy real-world inputs under rigorous security standards.
- Preferred postgraduate degree in machine learning, computer science, applied mathematics, or a related quantitative field.
- Preferred experience taking cutting-edge techniques from research papers into production.
- Preferred experience with AI evaluation or benchmarking frameworks and GraphRAG or knowledge graphs.
- Bonus familiarity with people analytics, HR technology, behavioral science applications, open-source contributions, or public technical writing.
Benefits
- Average of two days per week in a local Culture Amp office for most roles.
- Equity through the Employee Share Option Program.
- Learning programs and coaching.
- Quarterly refresh days, an extended end-of-year break, and a monthly wellbeing and lifestyle allowance.
- Inclusive parental leave from day one.
- MacBook and budget for setting up a home workspace.
- Five annual social impact days.
- Medical insurance coverage for employees and families in the US and UK.
Categories
About Culture Amp
Culture Amp helps organizations assess the readiness of their culture to achieve high performance and act with confidence in an AI-driven world. Powered by 15 years of People Science research and drawing on more than 1.6 billion data points, Culture Amp acts as an always-on intelligence layer, called the CultureOS™, that connects engagement, performance, employee experience and culture data into a single unified platform. Today, 25 million employees across 6,000+ organizations, including Canva, On, Asana, Dolby, McDonald's, and Nasdaq, depend on Culture Amp to drive culture-led performance as work and technology rapidly evolve. Learn more at cultureamp.com