[Remote] AI Engineer

Note: The job is a remote job and is open to candidates in USA. H2O.ai is a leading agentic AI company focused on democratizing AI through innovative solutions. They are seeking a Senior AI Engineer to design and implement end-to-end AI solutions for complex enterprise problems, working closely with customers and a team of experts to deliver impactful AI applications.

Responsibilities

• 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
• 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
• 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

Skills

• 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)
• 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
• 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

Benefits

• Remote-friendly culture with a flexible, high-trust working environment.
• Market-competitive total rewards package.
• Clear pathways for growth into senior technical leadership, architecture, or research roles.

Company Overview

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