AI Engineer - Applied AI

Culture Amp

Sydney

3 weeks ago

Sydney

3 weeks ago

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AI Engineer - Applied AI

AI Engineer - Applied AI role at Culture Amp in Sydney, focusing on building AI Coach systems. Requires commercial ML/AI production experience, full-stack development skills, and expertise in LLM applications. Hybrid work model with 2 days per week in office.

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Hybrid

Full-time

Senior

ML/AI Systems

Python

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid: average 2 days per week in local office

Employment Type

Full-time

Experience Level

Proven commercial experience taking ML/AI systems to production

Core Qualifications

Technical (Must-have)

ML/AI systemsPythonReactPGVectorLLM application developmentprompt engineeringcontext engineeringRAGagent architecturesLangGraph

Soft Skills

technical writingcommunicationproactivityhumilitypragmatic mindsetsolution-focusedcomfort with ambiguityfast iteration

Preferred Qualifications

Technical (Nice-to-have)

GraphRAGKnowledge GraphsNeo4jSpeech-to-TextText-to-SpeechWhisperElevenLabspeople analyticsHR techbehavioural science

Key Responsibilities

•Stay up to date with current research, literature and provider offerings
•Design, implement and evaluate areas and features of multi-agentic platform and systems using modern frameworks
•Advise, help build, and orchestrate data pipelines that unify fragmented workplace data into coherent coaching context
•Translate customer requirements into technical solutions and create technical documentation
•Partner closely with product, design, and people science to ensure features are fit for purpose
•Contribute to evaluation frameworks and bias testing to meet enterprise requirements for transparency and fairness
•Build cutting-edge, working prototypes integrated into environments to validate new approaches

AI EngineerApplied AISoftware DevelopmentEngineeringInformation TechnologyMachine LearningLLMPythonReactHybrid

Key Responsibilities

•Stay up to date with current research, literature and provider offerings

•Design, implement and evaluate areas and features of multi-agentic platform and systems using modern frameworks

•Advise, help build, and orchestrate data pipelines that unify fragmented workplace data into coherent coaching context

•Translate customer requirements into technical solutions and create technical documentation

•Partner closely with product, design, and people science to ensure features are fit for purpose

•Contribute to evaluation frameworks and bias testing to meet enterprise requirements for transparency and fairness

•Build cutting-edge, working prototypes integrated into environments to validate new approaches