Senior Manager, AI Engineering (AI)

Location: Sydney, Australia; hybrid work arrangement.

Company

hirify.global is an AI cloud platform company developing open-source and enterprise AI solutions, including agentic AI, predictive AI, SLMs, and Sovereign AI deployments.

What you will do

• Lead end-to-end delivery of AI/ML and GenAI solutions for enterprise customers across industries, including financial services.
• Own multiple concurrent AI workstreams, including scope, timelines, quality, delivery risks, dependencies, and business outcomes.
• Manage, mentor, hire, onboard, and develop a team of AI engineers and data scientists; own staffing and capacity planning.
• Translate customer business problems into technical solutions, including model design, architecture, deployment, and stakeholder communication from engineering to executive level.
• Stay hands-on by prototyping, reviewing and debugging code, and making and defending architecture decisions.
• Guide predictive ML and GenAI systems across data preparation, feature engineering, training, evaluation, deployment, monitoring, governance, and reusable accelerator development.

Requirements

• 8+ years of experience in data science, machine learning, AI engineering, or software engineering, including enterprise delivery experience.
• 2+ years leading technical teams through direct people management or sustained technical leadership of engineers and outcomes.
• Demonstrated experience hiring, mentoring, giving performance feedback, and developing engineers.
• Track record of running multiple concurrent enterprise engagements to time, quality, and budget.
• Strong hands-on foundation in predictive machine learning, including feature engineering, model development, evaluation, and interpretability.
• Experience building and deploying production AI systems, APIs, backend services, or ML-powered applications.
• Solid understanding of GenAI systems, including LLMs, SLMs, RAG, prompt engineering, evaluation, and agentic workflows.
• Strong Python skills and production engineering practices, including testing, CI/CD, debugging, version control, and system design.
• Experience with cloud platforms and MLOps/LLMOps concepts, including deployment, monitoring, and governance.
• Ability to review technical implementations, guide architecture decisions, and coach engineers to make decisions independently.
• Strong customer-facing communication skills, including whiteboarding with engineers and presenting to executive stakeholders.

Nice to have

• Experience with H2O products: Driverless AI, H2O-3, H2O Wave, h2oGPTe, or H2O LLM Studio.
• Technical consulting, solutions engineering, or AI delivery experience.
• Experience building or scaling a technical team or function.
• Experience managing distributed teams across time zones.
• Commercial experience with scoping, statements of work, estimation, and delivery margin accountability.
• Experience leading workshops, hackathons, or enterprise AI enablement programmes.
• Exposure to regulated industries such as financial services, healthcare, or insurance.
• Experience designing or reviewing full-stack AI applications or platforms.
• Contributions to Kaggle, open source, technical writing, or conference speaking.

Culture & Benefits

• Remote-friendly culture with a flexible working environment.
• Market-leading total rewards.
• Career growth opportunities.
• Inclusive culture and commitment to diversity.