Data Engineer – Python/AI

Role Overview

This role is responsible for developing and delivering data solutions to accomplish technology and business goals and initiatives. The Data Engineer will work with stakeholders and Product and Software Engineering teams to aid with implementing data requirements, analyzing performance, and researching and troubleshooting data problems within system engineering domains.

What You Will Do

Key responsibilities include performing code design and delivery tasks associated with the integration, cleaning, transformation, and control of data in operational and analytical data systems. The Data Engineer will design, build, and operate AI/ML solutions end-to-end, with strong emphasis on MLOps, ML lifecycle management, and production readiness.

Why It Might Be a Fit

The Data Engineer will work closely with product, operations, and engineering teams to build, deploy, and scale ML and GenAI solutions embedded into mission-critical platforms, while adhering to enterprise standards for security, compliance, and model governance.

Requirements

• Bachelor’s degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related
• 6+ years overall experience in software engineering with strong hands-on development in Python
• 3+ years of hands-on AI/ML experience, building and deploying machine learning models and Gen AI solutions using locally hosted LLMs in production environments
• Proven experience productionizing ML models using MLflow and enterprise-grade MLOps frameworks
• Strong understanding of the end-to-end ML lifecycle: data preparation, feature engineering, training, validation, deployment, monitoring, and retraining
• Experience building RESTful APIs and microservices to expose ML capabilities
• Hands-on experience with CI/CD pipelines, automation, and DevOps practices for ML and application workloads
• Experience with containerization and deployment technologies (e.g., Openshift, Docker or equivalent enterprise platforms)
• Proficiency with version control and enterprise SDLC tools (Git/Bitbucket, Jenkins, pytest, SonarQube, Artifactory, etc.)
• Experience working in large, multi-team enterprise environments with shared codebases and governance standards
• Strong analytical, problem-solving, and communication skills with ability to engage business and technical stakeholders

Benefits

• Dental insurance
• Vision insurance
• Flexible spending accounts
• 401(k) or pension plan
• Paid holidays
• Vacation time
• Sick leave
• Life insurance
• Disability insurance

Tagged as: Python