AI Engineer - Forward Deployed

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.

For more information, visit www.h2o.ai.

About This Opportunity

We are looking for a Senior 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 India.

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.
• Build production-ready applications independently: backend services, frontend interfaces, and the AI/ML layer connecting them
• 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.

Predictive AI & Machine Learning

• Rapidly build, iterate, and deploy multiple predictive ML models (classification, regression, time-series forecasting, anomaly detection) for enterprise customers
• Architect hybrid AI solutions that combine predictive ML (scoring, forecasting, classification) with Generative AI (natural language interfaces, RAG-based explanations, agentic orchestration)

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 (for both predictive models and LLM applications) and MLOps/LLMOps infrastructure that support continuous model improvement, automated retraining, drift detection, 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.
• Execute with a high degree of autonomy: taking full ownership to architect, prioritize, and ship production-grade solutions with minimal oversight.
• 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

• 4+ 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.
• Proven track record of rapidly building and deploying multiple predictive ML models - including classification, regression, time-series forecasting, or anomaly detection on structured/tabular enterprise data.
• Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) asnd 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.

Please visit www.H2O.ai to learn more.

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