Technical Lead

Future Secure AI

Brisbane

2 days ago

Brisbane

2 days ago

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Technical Lead

Future Secure AI seeks a Technical Lead to own the end-to-end creation of AI Co-Workers, leading technical design and implementation from concept to production. The role requires strong software engineering fundamentals, hands-on AI/ML experience, and leadership of small to medium teams. Based in Brisbane, Australia with hybrid work.

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Hybrid

Full-time

Lead

LLMs

Learned Models

Salary

Not specified

Work Location

Brisbane, Queensland, Australia, AU

Work Model

Hybrid

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

LLMslearned modelsintelligent automationbackend systemsAPIsdata flowsproduction architecturemodel selectionprompt designsystem architecture

Soft Skills

leadershipmentoringcommunicationownershiplearningcuriosityproblem-solvingpragmatic

Key Responsibilities

•Lead the technical design and implementation of AI Co-Workers from concept through production deployment
•Translate real business constraints into scalable AI and engineering solutions
•Own system architecture across models, orchestration logic, APIs, data pipelines, and integrations
•Lead technical decision-making for LLM usage, model selection, prompt design, evaluation, and monitoring
•Guide AI Engineers through build, test, and release cycles
•Partner closely with Engagement Leads to align technical execution with value delivery
•Ensure engineering quality across performance, reliability, security, and maintainability
•Identify technical risks early and drive pragmatic solutions in ambiguous environments
•Contribute hands-on to critical parts of the build while enabling the team to move faster

Technical LeadAIMachine LearningLLMSoftware EngineeringHybridBrisbaneAustraliaFull-timeLeadership

Key Responsibilities

•Lead the technical design and implementation of AI Co-Workers from concept through production deployment

•Translate real business constraints into scalable AI and engineering solutions

•Own system architecture across models, orchestration logic, APIs, data pipelines, and integrations

•Lead technical decision-making for LLM usage, model selection, prompt design, evaluation, and monitoring

•Guide AI Engineers through build, test, and release cycles

•Partner closely with Engagement Leads to align technical execution with value delivery

•Ensure engineering quality across performance, reliability, security, and maintainability

•Identify technical risks early and drive pragmatic solutions in ambiguous environments

•Contribute hands-on to critical parts of the build while enabling the team to move faster