[Hiring] Senior Python Developer: Databricks AI Platform, Alerting & Monitoring @Xenon7

Role Description

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

• 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.
• 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.).

Qualifications

• 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.

Requirements

• 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.

Benefits

• 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.