> Markdown version of [/jobs/ext/3652671-senior-ai-platform-ops-engineer](https://www.wearedevelopers.com/jobs/ext/3652671-senior-ai-platform-ops-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior AI Platform Ops Engineer

- **Company:** ASSOCIATE STAFFING LLC
- **Location:** Littleton, CO, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Database, Information Systems, Continuous Integration, Information Engineering, Data Governance, Identity and Access Management, Python (Programming Language), Machine Learning, Metadata Standards, Search Technologies, SQL Databases, Retrieval-Augmented Generation, Large Language Models, Amazon Virtual Private Cloud (VPC), Agentic-AI, Gitlab, Data Lakes, AI Platforms, Pyspark, Information Technology, Terraform, Data Pipelines, Databricks
- **Published:** October 9, 2026
- **Apply:** https://www.disabledperson.com/jobs/75921011-senior-ai-platform-ops-engineer

## About the Role

* Databricks production administration (Unity Catalog, Delta Lake design, cluster configuration, job orchestration)
 * Python + SQL + PySpark for reliable, scalable pipeline development
 * AWS platform fundamentals (IAM, S3, VPC) and ability to contribute to Terraform
 * Data governance implementation at scale (metadata standards, classification, lineage)
 * Platform operations and cost attribution/chargeback for usage-based environments

Nice to Have Skills

 * Databricks-native AI experience (Genie, Mosaic AI) or similar platform AI tooling
 * LLM enablement experience (RAG, vector search, agent frameworks, LLM-driven workflows)
 * CI/CD for Databricks deployments (Terraform, Asset Bundles, GitLab)
 * Databricks certifications (Data Engineering, Platform Administration, Machine Learning)
 * FinOps familiarity (cost allocation reporting, optimization practices)

Preferred Education and Experience

 * Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical field (or equivalent practical experience)
 * 5+ years in data engineering, platform engineering, or cloud data roles
 * 3+ years of hands-on Databricks production environment management

Other Requirements

 * Must be willing to participate in at least one in-person interview

## Description

Join an enterprise data and AI platform team where you'll drive the onboarding of new teams, data domains, and workloads onto a Databricks platform on AWS. In this senior, hands-on role, you'll set the technical patterns others follow-building secure integrations to external data sources, establishing Unity Catalog governance at scale, operationalizing Databricks-native AI capabilities (including Genie and Mosaic AI), and implementing cost attribution practices that enable smarter engineering decisions. This is an individual contributor role with meaningful technical leadership and cross-functional influence.