Senior AI Data Engineer | Databricks | MCP

We love technology, and we enjoy what we do. We are constantly driven by curiosity, innovation, and the desire to improve every day. We take ownership of our work, value collaboration, and foster a culture of trust and accountability. Our Enrouters embrace challenges, ask questions, learn quickly, and grow together.

We pride ourselves on offering competitive compensation, excellent benefits, a great work environment, flexible schedules, and policies that promote a healthy work-life balance. We care about who you are both inside and outside the workplace, and we are committed to building a strong community of driven, responsible, respectful—and above all—happy individuals. We want you to genuinely enjoy working with us.

We are seeking a highly versatile and strategic Senior AI Solutions Engineer (Data & Automation) to lead the design, development, and scaling of our enterprise Generative AI applications. In this role, you will be the bridge between our core data systems and modern serverless AI execution environments.

Rather than being locked into a single platform, you will have the architectural flexibility to leverage Google Cloud Platform (GCP), Amazon Web Services (AWS), or Databricks to build production-grade agentic solutions, automated serverless workflows, and retrieval systems. Your work will directly impact how our enterprise data is securely orchestrated, modeled, and exposed to foundational language models to automate complex business workflows.

Requirements

Serverless AI Architecture (Must-Have)

• Designing scheduled and event-driven serverless backends across equivalent cloud platforms.
• Architecting asynchronous worker systems utilizing message queues and event-driven pub/sub architectures.
• Deploying custom agents with orchestration frameworks (e.g., GCP Vertex AI Agent Engine/ADK, AWS Bedrock Agents, or Databricks Mosaic AI Agent Framework).

Equivalent ecosystem experience in at least one of the following:

GCP

• Cloud Run
• Cloud Functions
• Pub/Sub
• Eventarc
• Vertex AI Agent Engine / ADK

AWS

• Lambda
• ECS/Fargate
• SQS/SNS
• EventBridge
• Bedrock Agents

Databricks

• Serverless Workflows
• Serverless Jobs
• Mosaic AI Agent Framework

Enterprise RAG & Data Pipelines (Must-Have)

• Building secure, scalable Retrieval-Augmented Generation (RAG) pipelines across cloud environments.
• Constructing vector indexing, chunking, and layout-aware metadata extraction strategies.
• Managing governance, security, and access controls for data and model assets.

Equivalent ecosystem experience in at least one of the following:

GCP

• Vertex AI Vector Search
• Dataplex

AWS

• Amazon OpenSearch Service
• Amazon Bedrock Knowledge Bases
• AWS Glue

Databricks

• Mosaic AI Vector Search
• Delta Sync
• Unity Catalog

Integrations & AI Development (Must-Have)

• Integrating foundational LLM APIs into existing data pipelines and automated workflows.
• Containerizing applications and deploying secure custom tool interfaces (such as Model Context Protocol / MCP).
• Triggering downstream AI systems from BI platforms (e.g., Looker custom action hub) and SaaS platforms (e.g., Salesforce, Contentful).
• Advanced development experience in Python and SQL.

Platform Engineering & DevOps (Nice-to-Have)

• Managing Infrastructure as Code (IaC) configurations using Terraform.
• Familiarity with CI/CD automation pipelines (defining Jenkinsfiles or GitHub workflows).
• Implementing model monitoring, trace-based debugging, evaluation, and logging (e.g., MLflow, MLflow Tracing, or platform-equivalent tools).

Key Responsibilities

• Architect Agentic Solutions

• Build, deploy, and optimize autonomous and semi-autonomous AI agents capable of multi-step reasoning, planning, complex tool-calling, and secure data orchestration.

• Deploy Serverless Workflows

• Design and implement scalable scheduled and event-driven serverless workflows to automate business processes, data enrichment, classification, and document summarization.

• Optimize Data & Retrieval Systems

• Build, manage, and optimize enterprise-grade RAG retrieval pipelines, ensuring secure access to unstructured business data with scalable chunking, embedding, and indexing.

• Standardize Tooling & MCP

• Build, containerize, and deploy secure Model Context Protocol (MCP) servers and custom APIs to standardize how models securely interact with databases and external SaaS tools.

• Build SaaS & BI Integrations

• Bridge the gap between transactional and analytical tools by building custom integrations (e.g., Looker custom actions) that allow business users to trigger backend AI processes directly from their daily interfaces.

• Ensure Platform Governance & MLOps

• Maintain robust release pipelines via automated CI/CD and Terraform, while implementing complete tracking, debugging, and prompt evaluation systems (such as MLflow Tracing).

Benefits

• Monetary compensation
• Year-end Bonus
• IMSS, AFORE, INFONAVIT
• Major Medical Expenses Insurance
• Life Insurance
• Funeral Expenses Coverage
• TDU Membership
• MediAccess
• Health Check-Up Subsidy
• Preferential rates for car insurance
• Vacations
• Official Mexican Holidays
• Life Happens Days
• Bereavement Leave
• Civil Marriage Leave
• English Classes
• Certifications
• Educational Agreements (Talisis, U-ERRE, UNID, TecMilenio, Tec de Monterrey, UDEM, SPIS)
• Corporate Agreements & Discounts (Sorteos Tec, Envia Flores, TopGolf)
• Taquitos Rewards
• Birthday Bonus
• Work-from-home Bonus
• Laptop Policy

Equal employment:

Enroute is committed to providing equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.