Senior Python Developer: Databricks AI Platform, Alerting & Monitoring

About Xenon7 Where elite tech talent meets world-class opportunities! At Xenon7, we partner with leading enterprises and innovative startups on transformative projects across Data, Infrastructure, and AI. We are building an exclusive community of top-tier experts ready to solve real-world problems and shape the future of intelligent systems. Role Overview We are seeking a Senior Python Developer who thrives at the intersection of AI Platform Engineering and System Observability . This is a unique "hybrid" role where you will be responsible for building automated, scalable Databricks environments for AI/ML workloads, while simultaneously engineering a robust, Python-based AWS monitoring and alerting ecosystem. You aren't just building the engine; you are designing the high-tech dashboard and fail-safes that ensure it runs perfectly at scale. Key Responsibilities 1. Databricks Automation & AI Integration Workload Automation: Build Python-based workflows for MLOps, LLMOps, and application deployment within Databricks. Workspace Governance: Enhance workspace onboarding including Unity Catalog, permissions, and environment setup using reusable Python modules. AI Deployment: Integrate Mosaic AI components (Gateway, Model Serving, Agents) into platform automation. Architecture: Support Delta Lake (Bronze/Silver/Gold) architecture and MLflow model lifecycles. 2. Python-Driven Alerting & Monitoring Observability Frameworks: Implement automated health checks for AWS resources and Databricks applications. Event-Driven Alerting: Develop and configure alerting mechanisms using AWS CloudWatch, SNS, and EventBridge. Consistency & Compliance: Build Python automations to validate configuration consistency across multiple AWS accounts and detect anomalies or misconfigurations. Workflow Integration: Create automated service request workflows that bridge alerting with ticketing systems (Slack, Jira, etc.). Required Technical Expertise Python Mastery (6+ Years): Deep understanding of Python internals, including GIL behavior, multiprocessing vs. multithreading, and memory overhead trade-offs. Databricks Ecosystem: Hands-on experience with Unity Catalog, MLflow, and Mosaic AI. AWS Automation: Strong proficiency in AWS Lambda, API Gateway, CloudWatch, and EventBridge. Reliability Engineering: Experience with Docker image immutability, automated rollback strategies, and production stability patterns. Authentication: Experience with Service Principal-based authentication for secure Databricks/AWS bridging. Ideal Candidate Profile 6+ years of professional Python development and cloud automation experience. A dual mindset: You love building new AI capabilities but are equally obsessed with proactive monitoring and 99.9% uptime. Ability to work independently in a remote, global environment. Immediate availability is highly preferred. Ecosystem of Opportunity: Be part of a network where client engagements, thought leadership, and mentorship paths are interconnected. Outcome-Focused Culture: We value smart execution, autonomy, and ownership over "hours at a desk." Leading Edge: Contribute to projects that shape the direction of AI and high-scale cloud infrastructure.