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Lead end-to-end technical engagements to design, build, and deploy agentic AI and LLM-powered applications (RAG, fine-tuning, multi-agent systems). Own full ML lifecycle, backend services, integrations across cloud/on‑prem, and production LLMOps. Coordinate cross-functional teams, mentor junior engineers, and represent H2O.ai in customer workshops and executive briefings to deliver production-grade, compliant AI solutions.

Customer-facing role delivering end-to-end Generative/Agentic AI solutions: problem definition, data prep, model development, deployment, monitoring, LLM selection/fine-tuning/RAG, training workshops, and solution design using H2O tools to translate technical outputs into business value.

Design, build, and deploy end-to-end agentic AI and LLM applications for enterprise customers. Responsibilities include model development (RAG, fine-tuning), production ML pipelines, Kubernetes/Helm deployments (cloud, on-prem, air-gapped), LLMOps and monitoring, customer-facing technical delivery, troubleshooting, workshops, and ensuring secure, production-grade AI with guardrails and performance sizing.

Design, build, and maintain scalable back-end services (Python/Java/Go) and responsive front-end interfaces (React/TypeScript). Translate product concepts into technical designs, implement CI/CD pipelines, perform code reviews and testing, monitor and optimize production systems, and collaborate with cross-functional teams to deliver reliable cloud-native, microservices-based software.

As an AI Engineer, you will design and deploy AI solutions, including LLM applications, integrating them into enterprise environments, and collaborating with customers to resolve complex challenges.