From disconnected data to confident, explainable decisions

data2 delivers trustworthy, explainable AI (eXAI) that automates critical workflows and turns complexity into clarity. Our patented, hallucination-resistant eXAI re View platform harmonizes data across your ecosystem delivering real-time actionable insights.

As a Tier 3 - Support Engineer, you will own the most challenging technical escalations from our support team. Perform root cause analysis on complex system defects, data inconsistencies, and performance bottlenecks within the Graph RAG architecture.

Develop an expert-level understanding of our patented re View platform, including its graph database schemas, LLM integration points, vector search logic, and API layer.

Drive Cross-Functional Issue Resolution: By working directly with Support, Product, and Engineering to prioritize, validate, and co-own fixes. Analyze support trends to identify recurring issues and propose architectural or code-level changes to prevent them.

Manage Critical Incidents: Lead technical bridges during high-severity outages, coordinating with cloud engineering and development teams to restore service and communicate status.
Deep-Dive Debugging: Use advanced tooling to trace issues through the entire stack—from the user interface, through the API, into the graph queries, and down to the underlying cloud infrastructure.
Deep Technical Expertise: 3+ years of experience in a support engineering, SRE,



or Dev Ops role, with a proven ability to troubleshoot complex, distributed systems.
Systems Thinking: Ability to diagnose issues not just by looking at a single error, but by understanding the interplay between APIs, graph databases (Neo4j/ Memgraph ), vector indexes, and cloud infrastructure.
Strong proficiency in querying languages (Cypher, SQL) and a working knowledge of a programming language (Python, Java, or Go) to read logs, understand stack traces, and potentially write small scripts for data analysis.

Cloud & Infrastructure Knowledge: Hands-on experience with AWS or Azure, including familiarity with networking concepts, IAM roles, and services like EC2, S3, or Lambda for troubleshooting deployment issues.

Graph Database Expertise: Deep experience with graph data models and query optimization in Neo4j, Memgraph, or similar.
Understanding of the LLM lifecycle, vector databases, prompt engineering, and common failure modes of RAG(Retrieval-Augmented Generation) systems.
Experience with Observability Stacks: Proficiency with tools like Datadog, Grafana, Open Search, or Splunk for proactive monitoring and log analysis.
Experience with Jira, Confluence, and integrating customer feedback directly into the development workflow.
Certifications: AWS Certified Solutions Architect, or equivalent advanced cloud certification.

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📌 AWS Support Engineer (Ecatepec de Morelos)
🏢 Data2
📍 Ecatepec de Morelos