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# Sr AI Machine Learning Engineer

- **Company:** The Hartford
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $117,200.0 - $175,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Architectural Patterns, CA Workload Automation Ae, Unix, Cloud Computing, Cloud Engineering, Continuous Integration, DevOps, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Web Services, Enterprise Data Management, Large Language Models, Generative AI, Git, Cloudformation, Machine Learning Operations, Terraform, Jenkins
- **Published:** May 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f54f4547c27b9425

## About the Role

Do you have experience in UNIX?, Do you have a Master's degree?, * Must be authorized to work in the U.S. now and in the future.

 * Master's degree in related field or 5+ years of equivalent experience in a research or DevOps function.
 * Development experience developing solutions within AWS, GCP or both.
 * Experience developing repeatable architectural patterns; ability to identify redundancies and eliminate them with these patterns.
 * Experience building and deploying API services within the Cloud.
 * Experience building CICD pipeline using Jenkins or equivalent
 * Experience with IAC (Infrastructure as Code) including Cloud Formation, Terraform, or equivalents
 * Experience in Unix, git, and strong object oriented development experience using Python
 * Experience in end to end model development lifecycle, from ideation through post production monitoring.
 * Experience with workflow automation platforms (Apache Airflow, Autosys, similar)
 * Basic understanding of Data Science model development life cycle
 * Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM's into automated processes

## Description

* Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
 * Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
 * Review work with leadership and partners on an ongoing basis to calibrate deliverables against expectations.
 * Accountable for deployment design, development and maintenance of both traditional ML and AI models.
 * Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable presenting new concepts to technical audiences.
 * Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams
 * Delivery of critical milestones for model deployment in the AWS and GCP clouds.
 * Adopt and promote MLOps best practices to the Data Science community.


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