Senior Agentic AI Engineer
US-CO-Denver
Attract-careers1
Req #: 100523
Type: Fulltime-Regular
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Overview: 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. 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 Sr. Agentic AI Engineer role exists to lead technical onboarding of users, teams, and data domains onto EchoStar's enterprise Databricks platform on AWS. This role solves problems in external data source integration, Unity Catalog governance at scale, deployment of Databricks-native AI capabilities including Genie and Mosaic AI, and cost attribution across onboarding workloads. It is a senior individual contributor position with technical leadership expectations: setting the patterns other engineers follow, mentoring junior engineers, and owning the integration work that makes external data and AI capabilities accessible at enterprise scale. This is a hands-on role, not a management position, that requires deep Databricks platform expertise, production data engineering skill, and practical AI and ML platform knowledge. What Success Looks Like (Objectives) * Lead the technical onboarding of new users, teams, and business units onto the Databricks platform, defining the patterns other engineers follow and owning the quality bar for what a well-onboarded workload looks like * Architect and build integrations connecting enterprise data sources to the platform, serving as the technical lead on integration work that crosses organizational or system boundaries * Deploy and operationalize Databricks-native AI capabilities, including Genie and Mosaic AI, and evaluate new Databricks AI features for enterprise fit before recommending adoption * Own Unity Catalog architecture across onboarding workloads, setting and holding the governance bar for metadata standards, data classification, and lineage tracking. * Design and maintain cost attribution and chargeback practices that give engineering leadership the data needed to make resource decisions * Set technical direction for onboarding and integration workstreams, provide technical mentorship to engineers, review designs, and represent the platform team in cross-functional technical discussions Qualifications: Core Skills and Competencies (What you'll bring): * Advanced, hands-on experience administering Databricks at production scale, including Unity Catalog architecture, Delta Lake table design, cluster configuration, and job orchestration * Mastery of Python, SQL, and PySpark for building data pipelines that perform reliably under production load and hold up over time * Practical AI and ML platform knowledge, including LLM-driven workflows, retrieval-augmented generation, vector search, and agent framework infrastructure * Working knowledge of AWS services underpinning the platform, including IAM, S3, and VPC, along with the ability to read and contribute to Terraform configurations. * Practical experience with platform cost attribution, chargeback design, and usage-based resource management * Proven ability to set technical direction, mentor engineers, and represent the platform in cross-functional discussions, backed by strong written and verbal communication for both technical and business audiences Minimum Requirements: * Minimum Education: Bachelor's Degree in Computer Science, Information Technology, or a related field * Minimum Experience: 5 years of experience in Platform Engineering, DevOps, or Cloud Operations * Required Technical Skills: * Experience implementing Unity Catalog and data governance controls * Infrastructure-as-Code using Terraform * Python and PySpark for data pipeline design #LI-CH2LI
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