AI Automation Engineer

Databricks is the Data and AI company, trusted by over 20,000 organizations worldwide—including 70% of the Fortune 500—to build and scale data and AI applications, analytics, and intelligent agents. The company operates a unified platform that combines data infrastructure, analytics, and AI capabilities, with teams distributed across 30+ offices globally.

The Infrastructure team at Databricks is looking for an AI Automation Engineer to develop the next generation of intelligent automations that enhance how employees interact with internal systems and support services. This role focuses on building production-ready AI agents and automation services that interpret natural language requests, understand organizational context, and safely execute actions across enterprise tools—transforming repetitive IT interactions into self-service experiences powered by AI running on Databricks technology.

What you'll do

• Design, deploy, and operate AI agents that interpret employee requests, retrieve context from internal systems, select appropriate tools, execute actions, and report outcomes
• Maintain MCP servers and build multi-step agentic workflows that decompose complex goals, handle failures, request human approval when needed, and resume execution
• Ground AI agents in trusted internal knowledge including policies, runbooks, documentation, and standard operating procedures
• Convert high-volume, repetitive IT support interactions into reliable AI-powered self-service experiences
• Instrument automations with comprehensive logging, metrics, and feedback mechanisms
• Design automation systems incorporating identity governance, role-based access controls, human approval workflows, audit trails, and failure recovery
• Build shared automation infrastructure including credential management, event handling, scheduling, approval systems, and state stores for other teams
• Collaborate with IT Support, Employee Experience, Security, IAM, and Engineering teams to identify opportunities and move solutions from prototype to production
• Document system designs, operational procedures, and architectural decisions with technical clarity

What you'll bring

• Strong Python proficiency and hands-on experience with Git-based workflows, automated testing, and CI/CD pipelines
• Deep expertise with REST APIs, OAuth2 and authentication frameworks, event-driven integrations, and enterprise system connectivity
• Proven track record shipping production LLM-powered applications or AI agents into real-world environments
• Solid understanding of agent design patterns including tool calling, multi-step reasoning, context management, retrieval augmented generation, structured outputs, and goal decomposition
• Knowledge of LLM failure modes such as hallucination, incorrect tool selection, prompt injection, and non-deterministic outputs
• Experience using automated evaluations, tracing systems, test datasets, and human feedback to assess and improve AI systems
• Ability to translate ambiguous employee problems into simple, dependable technical solutions
• Strong judgment regarding security, privacy, least privilege principles, and safe automation in enterprise settings
• Excellent cross-functional collaboration and communication skills

Nice to have

• Experience building agents with Agent Bricks or frameworks like OpenAI Agents SDK, LangGraph, or LangChain
• Familiarity with MLflow tracing and evaluation, vector search technology, or LLM observability tools
• Prior work integrating IT platforms such as Okta, Microsoft Entra ID, Google Workspace, Jira, Slack, Jamf, GitHub, Workday, or SaaS administration APIs
• Knowledge of identity lifecycle management, access governance, device management, or software provisioning
• Experience with automation platforms like Tines, MuleSoft, or Workato

What they offer

• Full-time position based in Costa Rica
• Comprehensive benefits and regional perks tailored to employee needs