The MLOps Engineer will implement infrastructure and automation for scalable ML systems, ensuring compliance and efficiency in a startup environment.

Lead product strategy, design, and execution for AI platforms. Collaborate with stakeholders, build a product team, and ensure adoption of AI-driven tools.

As a Data Engineer, design and maintain data pipelines, ensure data quality, and support AI workflows using modern tools and cloud environments.

The Full Stack Data Engineer will design and implement end-to-end data pipelines, integrate core systems, build automated workflows, and support analytics and machine learning initiatives.

The Ontology Engineer will design and implement semantic models for a new data platform, ensuring data interoperability and collaboration with AI teams.

Design, build, and deploy machine learning and generative AI systems, transforming prototypes into production systems while collaborating with technical teams.

As a Full-Stack Engineer, you will build prototypes across frontend and backend, integrating AI capabilities, and collaborate with teams to transition them to production.

The Backend / Integration Engineer will design and build APIs and microservices for B2B platforms, ensuring integration with ERP, CRM, and eCommerce systems while utilizing AI tools.

The DevOps / Platform Engineer will manage CI/CD pipelines, infrastructure as code, and automation to enhance developer experience, while ensuring compliance and security in workflows.