AI Automation Engineer

Databricks
Costa Rica

Who this role is best for

Aimed at mid-to-senior-level engineers with AI automation experience who can collaborate across teams and work in a global enterprise environment.

Best fit for

  • Candidates with strong experience in building AI agents and enterprise system integrations
    — “Build AI agents and automations: Design, deploy, and run AI agents that support all of our employees.”
  • Individuals who can translate ambiguous employee problems into secure, reliable technical solutions
    — “Ability to translate ambiguous employee friction problems into simple, reliable technical solutions.”
  • Professionals with a background in automation platforms and REST APIs in enterprise settings
    — “Experience with automation or integration platforms (Tines, MuleSoft, Workato, etc.).”

Things to consider

  • The role requires working with enterprise systems and security frameworks in an international setting.
    — “Strong judgment around security, privacy, least privilege, and safe automation in an enterprise environment.”
  • Candidates must be prepared to maintain and develop MCP servers as part of the job.
    — “Experience with MCP (Model Context Protocol) server development.”

How to stand out

  • Highlight experience with agentic workflows and failure handling in your resume and interviews.
    — “Build agentic workflows that decompose goals into steps, handle failures, pause for human approval as needed, and resume their workflows.”
  • Showcase your ability to ground AI agents in enterprise policies and documentation.
    — “Ground agents in trusted internal knowledge (policies, runbooks, system documentation, SOPs, etc).”
  • Demonstrate your experience with instrumenting AI systems with logs and feedback loops.
    — “Instrument AI automations with logs, metrics, and feedback loops.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • building AI agents and automations
  • instrumenting AI automations
  • designing and implementing AI automations
Typical background
proficiency in Pythonexperience with Git-based developmentstrong experience with REST APIs

Skills & requirements

Required

PythonREST ApisOAuth 2.0Event-driven IntegrationsEnterprise System IntegrationsLlm-powered ApplicationsAI Agents

Preferred

Databricks Agent BricksMlflow Tracing/evaluationVector SearchLLM Observability

Stack & domain

PythonREST ApisOAuth 2.0Event-driven IntegrationsEnterprise System IntegrationsAIAutomationIT

About the role

Original posting from Databricks

GAQ427R224

About the role

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 agents in 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.

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.

Source: Databricks careers

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