Automation Engineer

Automation Engineer

Strong Python software development experience. Experience building automation tools, services, frameworks, or internal platforms. Experience working in a Data Engineering, Data Platform, AI Platform, or ML Platform environment. Experience with Databricks, Spark, or PySpark. Experience designing and developing scalable software solutions. Experience integrating with APIs, cloud platforms, or distributed systems. Experience with workflow orchestration platforms such as Airflow. Strong problem-solving and debugging skills.

Experience building production-quality code with testing, logging, and monitoring. Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.

Nice to Have

Skills & Experience:

Experience with AI Operations (AIOps), MLOps, or platform engineering. Experience with LLMs, Generative AI, RAG, semantic search, vector databases, or chatbot development. Experience building systems that allow users to query data using natural language. Databricks platform experience, including Unity Catalog, Delta Lake, or Delta Live Tables. Experience with cloud platforms such as AWS, Azure, or GCP. Experience with monitoring and observability tools such as Datadog, Grafana, Prometheus, Cloud Watch, or Splunk.

Experience with Kubernetes, Terraform, CI/CD, or Infrastructure as Code. Experience building operational dashboards, diagnostics platforms, or self-service tooling. Experience automating incident detection, remediation, or operational workflows. Experience with feature stores, model serving, or machine learning platform engineering.

Job Description:

This Automation Engineer role sits within a Data and AI Operations team focused on building software and automation solutions that improve the reliability, efficiency, and scalability of data and AI platforms. The role bridges software engineering, data engineering, and AI operations, with a strong emphasis on Python development, workflow automation, operational tooling, platform engineering, and enabling self-service experiences for users. This is not a traditional ETL-focused Data Engineer role.

The ideal candidate is a strong Python engineer who has worked in data engineering environments and enjoys building software that automates operational processes, improves developer productivity, and enables users to interact with data and platform systems more efficiently.

Day to Day:
Build Python-based tools and services that automate operational workflows. Develop software that improves the efficiency of data and AI platform operations. Create self-service solutions that allow users to ask questions and automatically retrieve answers from data and operational systems. Design and implement automation frameworks that reduce manual effort across data and AI workflows. Develop integrations with Databricks, Spark, Airflow, cloud platforms, and internal systems.

Build monitoring, diagnostics, and operational support tooling. Automate issue detection, root cause identification, and remediation workflows. Collaborate with Data Engineers, AI Engineers, and Platform teams to improve operational efficiency and platform reliability. Design scalable systems and participate in architecture discussions around data and AI platforms. Develop internal tools, APIs, and services that support AI Operations and platform automation initiatives.