Software Engineer at H2o.ai, Inc.

Ottawa, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

05 Jun, 26

Salary

120000.0

Posted On

07 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Go, React, JavaScript, AWS, Azure, GCP, CI/CD, DevOps, Distributed Systems, Generative AI, LLMs, ML Infrastructure, Containerization, Microservices, Prototyping

Industry

Software Development

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. For more information, visit www.h2o.ai. About This Opportunity H2O.ai is seeking a highly motivated Full Stack & Systems Software Engineer to join our H2OGPTe generative AI project team. This is a hands-on technical role for someone who thrives on solving complex problems, moves fast, and refuses to accept "no" as an answer. You'll be working at the intersection of cutting-edge generative AI and production systems, delivering end-to-end solutions that push the boundaries of what's possible. This is a hybrid position is based in Ottawa, Canada. What You Will Do Design, develop, and deploy full stack features for the H2OGPTe platform from concept to production. Build and maintain robust systems software using Python, Go, and React. Implement and optimize solutions across major cloud platforms (AWS, Azure, GCP). Own the complete development lifecycle including CI/CD pipelines, testing, deployment, and monitoring. Collaborate closely with ML researchers and engineers to productionize generative AI innovations. Debug complex distributed systems issues and deliver creative solutions under pressure. Contribute to architectural decisions that shape the future of our generative AI platform. Rapidly prototype new capabilities and iterate based on user feedback. What We Are Looking For Required Qualifications 2+ years of professional software engineering experience. Strong programming skills in Python, Go, and React (or demonstrated ability to quickly master new technologies). Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native architectures. Hands-on experience with CI/CD pipelines and DevOps practices. Proven ability to deliver features end-to-end, from design through deployment. Track record of learning quickly and adapting to new technologies and domains. Essential Attributes Can-do attitude: You see obstacles as puzzles to solve, not roadblocks. Ownership mentality: You take pride in delivering high-quality solutions and stand behind your work. Fast learner: You're energized by new challenges and technologies, especially in ML and generative AI. Team player: You collaborate effectively, share knowledge, and elevate those around you. Execution-focused: You bias toward action and deliver results consistently. Innovative mindset: You're excited about pushing boundaries in generative AI applications. Tech Stack Languages: Python, Go, React/JavaScript Cloud: AWS, Azure, GCP Domain: Generative AI, LLMs, ML infrastructure Tools: CI/CD pipelines, containerization, distributed systems How to Stand Out From the Crowd Experience with machine learning systems, frameworks, or infrastructure. Background in generative AI, LLMs, or related ML technologies. Familiarity with containerization (Docker, Kubernetes) and microservices architectures. Experience with scalable distributed systems and data processing pipelines. Open source contributions or personal projects demonstrating technical initiative. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth Base salary range: $100,000 - 120,000 CAD 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. #LI-Hybrid

Responsibilities

The engineer will design, develop, and deploy full stack features for the H2OGPTe platform, building and maintaining robust systems software using Python, Go, and React. This includes owning the complete development lifecycle, collaborating with ML researchers, and debugging complex distributed systems issues.