Responsibilities

Define and govern the AI & Automation architecture strategy for Database Platforms.

Lead the technical evolution of existing automation solutions and frameworks.

Design scalable, reusable, and maintainable automation architectures.

Drive adoption of GenAI capabilities to improve operational efficiency and engineer productivity.

Architect integrations with enterprise AI services such as Microsoft Copilot, Azure AI Foundry, Copilot Studio, AI Agents, RAG services, and Agentic AI platforms.

Establish development standards, governance, security controls, observability, and best practices.

Collaborate with Database Engineering, Cloud, Security, Architecture, and AI teams.

Mentor engineers and provide technical leadership for AI and automation initiatives.

Skills Must have

Mandatory skills

8+ years in IT, including at least 3 years in an architect or technical lead role (solution, automation or platform architecture)

5+ years of hands-on database platform work as a DBA, database engineer or DBRE on Oracle and/or IBM DB2, plus PostgreSQL or MS SQL Server, in large estates (hundreds or thousands of instances)

Proven, hands-on design and implementation of database lifecycle automation: provisioning, patching and upgrades, backup and restore, health checks, failover and compliance reporting

Ansible: personally written roles and playbooks for database or infrastructure automation, including inventory, secrets and testing

Terraform: reusable modules, state management and multi-environment deployments (Azure, AWS and/or GCP)

CI/CD with GitHub and GitHub Actions (reusable workflows, environments and approvals, secrets, self-hosted runners), or Azure DevOps with readiness to work in GitHub Enterprise





Python and PowerShell scripting for automation and tooling

Hands-on delivery of at least one GenAI solution in production (LLM application, RAG or AI agent), including prompt engineering, grounding, evaluation and guardrails

Hands-on experience with the Microsoft AI stack: Azure OpenAI and/or Azure AI Foundry, Microsoft Copilot or Copilot Studio

Experience with Microsoft Azure and AWS, including REST API integration and event-driven or microservices architectures

Defining automation standards, reusable frameworks and governance (security, observability, code review) used by multiple engineering teams

Ability to clearly explain personal role, decisions and measurable outcomes on previous projects.

Nice to have

Automated Oracle or DB2 patching and version upgrades, including HA setups (Oracle RAC or Data Guard, DB2 HADR)

Database version-compatibility and upgrade-readiness assessments at scale

Automation of managed cloud databases (AWS RDS, GCP Cloud SQL, Azure SQL)

NoSQL databases on AWS or GCP

ServiceNow integration, such as exposing automation through Service Catalog with approval workflows

Platform engineering or internal developer platform experience (paved or golden paths, self-service tooling)

MCP (Model Context Protocol): building or integrating MCP servers

AI agents that execute operational actions with human-in-the-loop approval, RBAC and audit trails

Microsoft 365 Copilot extensibility

Vector and semantic search

AI orchestration frameworks

GCP experience

Security-by-design practices and threat modelling

Certifications: Azure Solutions Architect Expert (AZ-305), Azure AI Engineer Associate (AI-102), AWS Solutions Architect, TOGAF, Oracle OCP / DB2 DBA, HashiCorp Terraform Associate, Red Hat Ansible certification

📌 Database Architect (México)
🏢 Luxoft
📍 México