[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
Company H1B Sponsorship