About the job
About Us:
At Xenon7, we connect elite tech talent with exceptional opportunities! Collaborating with top enterprises and innovative startups, we engage in groundbreaking projects that harness the latest technologies across various IT domains, including Data, Web, Infrastructure, AI, and more. Our proficiency in IT solutions development and flexible resource allocation allows us to partner with clients on transformative initiatives, driving innovation and business growth. We are committed to delivering advanced solutions that tackle today's most complex challenges, empowering global organizations and supporting pioneering startups alike.
Join us in building a community of elite professionals as we welcome an exclusive group of outstanding AI & ML Professionals ready to address real-world challenges and shape the future of intelligent systems.
Role Overview:
We are on the lookout for a seasoned Databricks Automation & AI Platform Engineer with extensive knowledge in Python, Databricks platform components, and AI/MLOps/LLMOps workflows. This engineer will play a crucial role in supporting the Next‑Gen Platform Integration team by constructing automation frameworks, facilitating scalable deployment workflows, and embedding AI capabilities across Databricks environments.
This position demands strong systems-level Python expertise, experience with Databricks governance, and hands-on automation skills within AWS environments.
Key Responsibilities:
- Databricks Automation & Integration:
- Design and implement automation workflows for MLOps, LLMOps, and application deployment within Databricks.
- Enhance workspace onboarding automation, including Unity Catalog, permissions, and environment setup.
- Create reusable modules for workspace provisioning, catalog configuration, model deployment, and governance workflows.
- Integrate Mosaic AI components (Gateway, Model Serving, Agents) into platform automation.
- Platform Engineering & Deployment:
- Develop Python automation scripts for Databricks services such as Unity Catalog, MLflow, Mosaic AI, Model Serving, and Databricks Apps.
- Ensure consistency, reliability, and scalability across multi-workspace environments.
- Implement automated rollback strategies, fail-fast mechanisms, and environment stability checks.
- AWS Integration & Automation:
- Create integrations using AWS Lambda, API Gateway, and Service Principal authentication.
- Automate Databricks Job orchestration, monitoring, and deployment pipelines.
- Establish secure and scalable automation that bridges AWS and Databricks.
