H2O.ai is on a mission to democratize AI for Good. As the world’s leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control.
Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH.
For more information, visit www.h2o.ai.
About This Opportunity
We are looking for a Senior Manager, AI Engineering who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one.
You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes.
This position is based in Sydney, Australia.
What You Will Do
- Lead end-to-end delivery of AI/ML and GenAI solutions for enterprise customers across industries such as financial services.
- Own delivery execution across multiple concurrent AI workstreams, ensuring scope, timelines, quality and business outcomes are met.
- Manage, mentor and grow a team of AI engineers and data scientists, owning hiring, onboarding, performance management and career development.
- Own staffing and capacity planning across engagements, matching skills to accounts and clearing blockers for the team.
- Manage technical delivery risks, dependencies and coordination across engineering, data science, product and customer teams.
- Partner with customers to translate business problems into technical AI solutions, including model design, architecture and deployment approach.
- Stay hands-on: prototype, review and debug code, and make and defend architecture decisions.
- Guide design and review of ML models (predictive ML, time series, classification, clustering) and GenAI systems (LLMs, SLMs, RAG, prompt engineering, evaluation, agentic workflows).
- Ensure best practices across the ML lifecycle: data preparation, feature engineering, training, evaluation, deployment, monitoring and governance.
- Raise the technical bar across the team through design and code reviews, pairing and structured feedback.
- Act as the primary technical point of contact and escalation point for customers, balancing delivery execution with stakeholder management from engineer to executive level.
- Partner with sales and pre-sales on scoping, estimation, statements of work and expansion opportunities.
- Collaborate with product and engineering teams to build reusable accelerators and reference architectures, and feed field learnings back into the roadmap.
- 8+ years in data science, machine learning, AI engineering or software engineering, with enterprise delivery experience.
- 2+ years leading technical teams, either through direct people management or sustained tech-lead ownership 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, including 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 (testing, CI/CD, debugging, version control, system design).
- Experience with cloud platforms and MLOps/LLMOps concepts (deployment, monitoring, governance).
- Ability to review technical implementations and guide architecture decisions, and to coach engineers to make those decisions independently.
- Strong customer-facing communication skills, comfortable moving between whiteboarding with engineers and presenting to executive stakeholders.
How to Stand Out From the Crowd
- Experience with H2O products (Driverless AI, H2O-3, H2O Wave, h2oGPTe, H2O LLM Studio).
- Prior experience in technical consulting, solutions engineering, or AI delivery roles.
- Experience building or scaling a technical team or function, not just inheriting one.
- Experience managing distributed teams across time zones.
- Commercial exposure: scoping, SOWs, estimation, and accountability for delivery margin.
- Experience leading workshops, hackathons, or enterprise AI enablement programmes.
- Exposure to regulated industries (financial services, healthcare, insurance).
- Experience designing or reviewing full-stack AI applications or platforms.
- Contributions to Kaggle, open source, technical writing, or conference speaking.
Why H2O.ai?
- Market leader in total rewards
- Remote-friendly culture
- Flexible working environment
- Be part of a world-class team
- Career growth
H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.
H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We’ve made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence.
H2O.ai employs the world’s top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company’s purpose.
Please visit www.H2O.ai to learn more.
Skills Required
- 8+ years of experience in data science, machine learning, AI engineering, or software engineering with enterprise delivery experience
- 2+ years leading technical teams through direct people management or sustained technical leadership
- Experience hiring, mentoring, providing performance feedback, and developing engineers
- Experience running multiple concurrent enterprise engagements on schedule, within quality standards, and within budget
- Strong hands-on experience with predictive machine learning, feature engineering, model development, evaluation, and interpretability
- Experience building and deploying production AI systems, APIs, backend services, or ML-powered applications
- 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 or LLMOps concepts including deployment, monitoring, and governance
- Ability to review technical implementations, guide architecture decisions, and coach engineers
- Strong customer-facing communication skills with engineers and executive stakeholders
- Experience with H2O products such as Driverless AI, H2O-3, H2O Wave, h2oGPTe, or H2O LLM Studio
- Prior experience in technical consulting, solutions engineering, or AI delivery
- 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 programs
- 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
What We Do
H2O.ai is the leading AI cloud company, on a mission to democratize AI for everyone. Customers use the H2O AI Hybrid Cloud platform to rapidly make, operate and innovate to solve complex business problems and accelerate the discovery of new ideas. H2O.ai is the trusted AI partner to more than 20,000 global organizations, including AT&T, Aegon/ Transamerica, Allergan, Bon Secours Mercy Health, Capital One, Commonwealth Bank of Australia, GlaxoSmithKline, Hitachi, Kaiser Permanente, PayPal, PWC and Walgreens, over half of the Fortune 500 and one million data scientists. Goldman Sachs, NVIDIA and Wells Fargo are not only customers and partners, but strategic investors in the company. H2O.ai’s customers have honored the company with a Net Promoter Score (NPS) of 78— the highest in the industry based on breadth of technology and deep employee expertise. The world’s top 20 Kaggle Grandmasters (the community of best-in-the-world machine learning practitioners and data scientists) are employees of H2O.ai. A strong AI for Good ethos to make the world a better place and Responsible AI drive the company’s purpose. Please join our movement at www.H2O.ai.
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