Agentic AI Engineer II

Company Summary EchoStar is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV. Department Summary Our Technology teams challenge the status quo and reimagine capabilities across industries. Whether through research and development, technology innovation or solution engineering, our team members play a vital role in connecting consumers with the products and platforms of tomorrow. Job Duties and Responsibilities Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.   The Agentic AI Engineer role exists to scale and secure the enterprise Databricks platform on AWS that supports EchoStar's production analytics, machine learning, and AI agent workloads. This role solves problems in platform reliability, data governance under Unity Catalog, CI/CD automation, and the integration layer for AI agent frameworks including MCP servers. The team is building the foundational platform layer that EchoStar's GenAI products run on, so decisions made in this role carry direct impact on AI product velocity, security posture, and governance compliance across the enterprise. This is a hands-on engineering position that requires production Databricks experience, infrastructure automation skills, and genuine interest in AI platform governance.   What Success Looks Like (Objectives) Provision, manage, and continuously improve Databricks workspaces at production scale using Terraform and automated deployment patterns, and take ownership of platform monitoring and incident response Standardize Unity Catalog adoption across the platform, applying data sensitivity classifications including PII, CPNI, and PCI so access control stays consistent and auditable Support the integration of AI agents into the platform by implementing and maintaining Model Context Protocol (MCP) server frameworks and managing authentication for agentic access patterns Build and maintain CI/CD pipelines for Databricks Asset Bundle deployments, and reduce manual toil through self-service tooling on the team's internal developer portal Enforce cluster policies and contribute to cost attribution efforts that connect platform spend to the workloads and teams responsible for it Provide technical guidance to junior team members and document platform patterns that strengthen the team's shared knowledge base Skills, Experience and Requirements Core Skills and Competencies (What you’ll bring): Critical experience administering Databricks in a production environment, including workspace management, cluster configuration, Unity Catalog governance, and job orchestration Strong Python and Bash scripting ability applied to real automation problems, along with working knowledge of Terraform and CI/CD pipeline design Working knowledge of AWS services relevant to a cloud-native data platform, including IAM, S3, and VPC, gained through experience operating infrastructure in a regulated enterprise environment AI literacy spanning how ML models are served, what agent frameworks require from infrastructure, and how access patterns for AI workloads differ from batch analytics   Minimum Requirements: Minimum Education: Bachelor’s Degree in Computer Science, Information Technology, or a related field Minimum Experience: 3 years of experience in Platform Engineering, DevOps, or Cloud Operations Required Technical Skills: * Databricks administration and operation in production environments Infrastructure-as-Code using Terraform Cloud platform services (AWS S3, IAM, VPC) Python or Bash scripting for automation   Visa sponsorship not available for this role   #LI-CH2 Salary Ranges Compensation: $100,980.00/Year - $136,625.00/Year Benefits We offer versatile health perks,