Role Description Insurance is one of the world's largest industries and one of the most painful to interact with. Paper forms. Sluggish call centres. Three-week underwriting cycles. Claims that vanish into queues. We are rebuilding all of it on top of a modern platform and AI agents that actually do the work, not pretend to. You will not be picking up tickets. You will be deciding what to build, prototyping it on Monday, shipping a draft to a real customer by Friday, and improving it from real usage. We expect you to push the product, the codebase, and the way we work. We are looking for someone who treats AI as a creative material, not a feature on a roadmap. The next year of insurance is being defined right now. What gets automated, what gets reimagined, what gets thrown out. We want builders who want to be in that room and ship the answer. The team is small. The mandate is large. If your highest-energy work has historically come from solving real problems end to end, this is the seat. What You Will Do - Own outcomes, not tickets. Pick the biggest lever for our customers each sprint and drive it to live. Surface the next one yourself. - Build with AI as a primary tool, not a chatbot bolt-on. OCR, document understanding, generation, agent loops, evaluation harnesses. You decide where each fits. - Ship prototypes fast, then make them production-grade. A working demo on day three beats a perfect plan on day ten. - Work directly with customers. You will see real claims, real underwriting screens, real broker workflows. You will watch users hit dead ends and decide what to fix. - Raise the bar on the codebase. Reviews, refactors, testability, observability. Not as policy, as habit. - Push the team forward. Skills, agents, internal tools, engineering standards. Propose them, build them, get them adopted. Who You Are - You ship. Ideas without execution do not count for you. - High agency. You do not wait for a card to be assigned. You see what is worth doing and you start. - Strong opinions, loosely held. You make calls with incomplete information and change your mind when the evidence shifts. - Curious about the domain. Insurance is messy and full of weird incentives. That intrigues you, not annoys you. - Fluent with AI. You have shipped something real with LLMs or agents. You know where the magic ends and where you have to engineer carefully. - Care about humans on the other end. Insurance done right gives people peace of mind in their worst weeks. That is the point. Your Toolbox - Node.js + TypeScript + Nest.js on the back end - Vue (and some React) on the front end - GraphQL, MongoDB, Docker, AWS - AI work spans OpenAI, Anthropic, Google, plus a growing set of in-house skills and agents - You do not need to have used every piece. You do need to be the kind of engineer who picks up a new tool and is shipping with it within the week. What We Expect at This Level - 6+ years building production systems. Track record of complex, customer-facing software shipped, not just maintained. - Real AI experience. You have built and shipped at least one substantive AI-driven feature. POCs that died in a notebook do not count here. - Strong fundamentals. OO, design patterns, testing, web security, performance. You do not need a refresher. - Cloud comfort. AWS, Azure, or GCP. At least one in depth, the rest enough to hold a conversation. - Communication. You can explain a tradeoff to a non-technical stakeholder in two minutes and to an engineer in one. Not Suitable for the Role If… - You prefer tickets assigned to you over choosing what to build. - You measure your work in lines of code, not outcomes. - You see AI as a buzzword to put on your CV rather than a tool you have actually used in anger. - You want a process-heavy environment with detailed specs handed down from product. - You are looking for a maintenance role on a finished platform. Why CoverGo Insurance is the rare industry where AI can save people hours of their worst weeks. We are already shipping AI-powered claims, underwriting, distribution, and document automation to enterprise carriers across five continents. The platform is real. The customers are real. The next chapter is yours to help write. Why You'll Love Working Here - 100% Remote Work - 15 Days of Annual Leave - Annual Performance Bonus - Remote Work Allowance - Anniversary Bonus - Health Insurance - Company Activities and Events - Learning and Development Plan By submitting your application, you confirm that you have read, understood, and accepted the content of CoverGo’s Privacy Notice and you consent to the processing of your data as part of this application.

• Collaborate with cross-functional teams to design and build stateful, multi-agent workflows • Engage with clients to define requirements and oversee the full software development lifecycle • Implement rigorous evaluation pipelines to quantitatively measure agent performance • Proactively drive productivity and adapt to evolving demands • Translate stakeholders’ needs into requirements and drive development to ship prototypes • Stay informed about rapid advancements in the field

• Go to the field: talk to users, shadow their workflows, capture the as‑is → goals & constraints. • Define hypotheses & KPIs (precision/recall, FPR, TAT, coverage, cost/decision) and turn them into experiment plans. • Design decision flows that mix LLMs, retrieval/RAG, classical ML, and lightweight rules; ensure explainability and auditability. • Build quick prototypes (notebook → lightweight service/API) and measure their impact on real data. • Create evaluation sets and scoring rubrics (offline + side‑by‑side + sanity checks + guardrails). • Present findings & recommendations directly to decision‑makers; propose rollout (pilot → production‑lite → scale). • Lead innovation processes across the company; test, promote solutions and mentor others with new AI technologies.

Title: Senior AI Engineer Location: Sydney Australia Job Description: Founded in 2012, H2O.ai is on a mission to democratize AI. 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 GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our 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, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. About This Opportunity We are looking for an AI Engineer 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 Agentic AI & LLM Engineering - Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step workflows for enterprise customers. - Develop and deploy LLM-powered applications using techniques including RAG, fine-tuning, prompt engineering, function calling, and tool use. - Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. - Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best of it into customer engagements. End-to-End AI Application Development - Own the full development lifecycle: from problem framing and data exploration through model development, API integration, and production deployment. - Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. - Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. - Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Customer Engagement & Delivery - Work directly with customer data scientists, engineers, and business stakeholders to translate real-world problems into AI solutions. - Contribute to pre-sales and proof-of-concept engagements - building fast, credible demonstrations that win technical trust. - Communicate clearly across audiences: from detailed technical design reviews with engineering teams to outcome-focused updates for business stakeholders. - Collaborate closely with Program Managers, Solution Engineers, and Kaggle Grandmasters to deliver cohesive, high-quality solutions. What We Are Looking For Experience & Background - 3+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. - Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. - Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). - Experience deploying models and AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities - Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. - Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. - Backend development skills: REST APIs, containerization (Docker/Kubernetes), and CI/CD pipelines for AI applications. - Strong problem-solving instincts - comfortable with ambiguity, able to move fast without sacrificing engineering quality. - Clear communicator who can explain complex AI systems to non-technical stakeholders without oversimplifying. How to Stand Out From the Crowd - Kaggle or competitive ML experience. - Familiarity with H2O.ai products, Wave, or H2O Document AI. - Experience in financial services, healthcare, or other regulated industry AI deployments. - Exposure to tabular foundation models, AutoML, or enterprise ML platforms. - Prior experience in a customer-facing or field engineering role. 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. #LI-Hybrid