Senior Applied AI Engineer — Ship Agentic AI at Scale

United States Digital Space LLC

Sydney

Hybrid

AUD 150,000 - 210,000

Full time

13 days ago

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Benefits offered by this job

Equity

Learning programs

Quarterly refresh days

Parental leave

MacBook

Wellbeing budget

Medical insurance

Job summary

Culture Amp is seeking a Senior Applied AI Engineer to join the Frontier team, building agentic AI solutions at scale. You’ll translate cutting-edge techniques into production features that improve how people experience work.

Enjoy working at the intersection of applied AI research and product engineering, shipping real customer solutions. You’ll own end-to-end responsibilities from prompt engineering to system monitoring, collaborate with product, design and people science, and ensure

Qualifications

Proven commercial experience taking ML/AI systems to production.
Hands‑on experience with knowledge graphs and graph databases (e.g. Neo4j, Neptune).
Production LLM evaluation and observability: Langfuse, LangSmith, etc.
Experience in designing and scaling production-grade multi-agent systems (orchestration, prompt and context engineering, RAG, memory, agent architectures).

Responsibilities

Design, implement and evaluate areas and features for agentic AI capabilities and systems using frameworks (e.g., LangGraph) for stateful, multi-turn conversations.
Advise, help build, and orchestrate data pipelines and integrations involving workplace data (surveys, goals, performance reviews, feedback, 1-1 notes) into coherent context view.
Build memory across sessions, and context graph, grounded in a custom ontology, alongside per-user relational and procedural memory and preferences that persist to the user profile.
Build and evaluate effective RAG, including pre-processing and hybrid search, and design areas of our graph-based agentic frameworks.
Own the end-to-end feedback loop: prompt engineering, evaluation at scale, and continuous improvement, including LLM-powered analysis tools that diagnose performance shifts and recommend prompt or system-level changes.
Translate customer requirements into technical solutions by working backwards from user needs to system design, and write the technical documentation that supports transfer to product teams.
Partner closely with product, design, and people science so features are fit for purpose and scale.
Contribute to evaluation frameworks and bias testing that meet enterprise requirements for transparency, fairness, and responsible AI.
Create and Monitor guardrails and safety in production.
Stay current with AI research, literature and provider offerings, and bring what's useful into production.