Strategic Overview
AI Automation Engineer at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Build AI agents and automations: Design, deploy, and run AI agents that support all of our employees. The agents interpret natural-language requests, gather context, select tools, execute actions, and communicate outcomes. Maintain MCP servers across our AI…
The role is listed for Costa Rica with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
GAQ427R224
We're hiring an AI Automation Engineer to build the next generation of IT automations to improve the employee experience at Databricks.
You'll be building production-grade AI agents and automation services that understand employee requests, retrieve enterprise context, reason across systems, invoke tools and APIs, and take action safely. The goal isn't to automate existing workflows the same way we've done it for the past decade. It's to reimagine how employees interact with IT through intelligent, contextual, and increasingly agentic experiences…
Key Responsibilities & Objectives
- Build AI agents and automations: Design, deploy, and run AI agents that support all of our employees. The agents interpret natural-language requests, gather context, select tools, execute actions, and communicate outcomes.
- Maintain MCP servers across our AI tools portfolio.
- Build agentic workflows that decompose goals into steps, handle failures, pause for human approval as needed, and resume their workflows.
- Ground agents in trusted internal knowledge (policies, runbooks, system documentation, SOPs, etc).
Required Qualifications & Candidate Blueprint
- Experience with Git-based development, automated testing, and CI/CD.
- Strong experience with REST APIs, OAuth2/authentication frameworks, event-driven integrations, and enterprise system integrations.
- Experience with agent patterns: tool/function calling, multi-step workflows, context management, RAG, structured outputs, and plan decomposition.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
GAQ427R224
We're hiring an AI Automation Engineer to build the next generation of IT automations to improve the employee experience at Databricks.
You'll be building production-grade AI agents and automation services that understand employee requests, retrieve enterprise context, reason across systems, invoke tools and APIs, and take action safely. The goal isn't to automate existing workflows the same way we've done it for the past decade. It's to reimagine how employees interact with IT through intelligent, contextual, and increasingly agentic experiences and to do it on Databricks.
What you will do
- Build AI agents and automations: Design, deploy, and run AI agents that support all of our employees. The agents interpret natural-language requests, gather context, select tools, execute actions, and communicate outcomes.
- Maintain MCP servers across our AI tools portfolio.
- Build agentic workflows that decompose goals into steps, handle failures, pause for human approval as needed, and resume their workflows.
- Ground agentsin trusted internal knowledge (policies, runbooks, system documentation, SOPs, etc).
- Turn high-volume support CUJs into self-service experiences: Identify repetitive, high-friction IT interactions and convert them into reliable AI automation experiences.
- Instrument AI automations with logs, metrics, and feedback loops.
- Design and implement AI automations with identity governance, tools RBAC, human-in-the-loop approvals where applicable, audit trails, and failure handling.
- Create shared automation infrastructure (credential vaults, event ingestion, scheduling, approval workflows, cache/state stores) that other teams can build on.
- Work with IT Support, Employee Experience, Security, IAM, Infrastructure, and Engineering to identify automation opportunities and take solutions from prototype to production.
- Write and maintain high-quality technical/engineering documentation that clearly communicates system designs, operational procedures, and architectural decisions.
What we are looking for
- Proficiency in Python or Go [3yrs].
- Experience with Git-based development, automated testing, and CI/CD.
- Strong experience with REST APIs, OAuth2/authentication frameworks, event-driven integrations, and enterprise system integrations.
- Shipped production LLM-powered applications or AI agents.
- Experience with agent patterns: tool/function calling, multi-step workflows, context management, RAG, structured outputs, and plan decomposition.
- Understanding of LLM failure modes: hallucination, incorrect tool use, ambiguous intent, prompt injection, excessive permissions, and non-deterministic behavior.
- Experience evaluating and improving AI systems using automated evals, traces, test datasets, human feedback, or similar approaches.
- Ability to translate ambiguous employee friction problems into simple, reliable technical solutions.
- Strong judgment around security, privacy, least privilege, and safe automation in an enterprise environment.
- Strong collaboration and communication skills. You will work cross-functionally to plan, design, and implement automation together.
- Experience with automation or integration platforms (Tines, MuleSoft, Workato, etc.).
- Experience with MCP (Model Context Protocol) server development.
Nice to have
- Experience building agents on Databricks (Agent Bricks) or with frameworks such as OpenAI Agents SDK or LangGraph/LangChain.
- Experience with MLflow tracing/evaluation, vector search, and LLM observability.
- Experience integrating IT platforms: Okta/Microsoft Entra ID, Google Workspace, Jira, Slack, Jamf, GitHub, Workday, or SaaS administration APIs.
- Familiarity with identity lifecycle, access management, device management, and software provisioning.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Build AI agents and automations: Design, deploy, and run AI agents that support all of our employees. The agents interpret natural-language requests, gather context, select tools, execute actions, and communicate… — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.