DevOps Engineer

Role Overview

We are seeking a hands-on technical leader to implement and operationalize distributed graph computing solutions. You will focus on Entity Resolution, Network Generation services, CI/CD pipelines, and Kubernetes orchestration for our next-generation data intelligence platform.

Key Responsibilities

• Infrastructure as Code: Use Terraform and Kubernetes to manage microservices lifecycles ensuring reproducible environments.
• DataOps & Platform Integration: Streamline ingestion of billions of records using Spark-based pipelines and automated deployment of blocking strategies (e.g., LSH).
• Auditability & Monitoring: Implement comprehensive monitoring, logging, and alerting stacks to track model drift and pipeline health.
• AI/ML & Explainability: Operationalize Graph Neural Networks (GNNs) using neighbor sampling for fraud analysis, semantic resolution via fuzzy matching, and champion model transparency with SHAP/LIME integration.

Minimum Qualifications

• Masters in Computer Science or related field.
• +5 years experience in distributed computing and big data systems (Apache Spark).
• Proficiency in DevOps toolchains (Terraform, Kubernetes) for microservices deployment.

This role offers significant early-stage equity, flexible remote-first culture, and the chance to shape core engineering decisions at an innovative AI startup. Join us to solve intricate technical challenges that push boundaries with distributed graph computing!