Senior Associate - AI Engineer

New York Life Insurance Co•New York, NY

12d•$124,000 - $177,000•Hybrid

About The Position

New York Life’s AI and Data team delivers innovative data, insights, and AI solutions across the organization. The AI team works on a diverse portfolio of AI and GenAI initiatives, combining agile and entrepreneurial ways of working with industry-leading methods and tools. Our efforts are fully supported by executive leadership, and we partner closely with business stakeholders through all stages of model development—from ideation to deployment. The team brings together product managers, data scientists, MLOps engineers, program managers, model validation and governance experts, and communications and development professionals. You will contribute to the design, build, and maintenance of a platform that enables the development and deployment of AI and Data solutions, helping to evolve and support an industry-leading MLOps technology stack.

Requirements

6+ years of industry experience in software engineering, data engineering, DevOps, MLOps, or a related field
Expert-level experience with cloud compute environments, particularly AWS, and cloud-native tools; Terraform proficiency required
Hands-on experience with containers (Docker), container orchestration (Kubernetes), and workflow orchestration/DAGs (e.g., Airflow)
Strong experience with AWS services such as EKS, EC2, S3, IAM, and CloudWatch; familiarity with SageMaker or similar platforms is a plus
Solid understanding of CI/CD and DevSecOps best practices, including Git branching strategies, pull requests, code reviews, and artifact or security scanning (e.g., Jenkins, GitHub Actions, GitLab CI)
Good command of SQL with familiarity working with relational databases
Experience supporting both batch and real-time inference using REST, gRPC, or streaming architectures
Proficiency in Python and Bash, with working knowledge of infrastructure-as-code tools such as Terraform and Helm
Agile mindset with experience working in iterative, collaborative delivery models
Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across teams
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Nice To Haves

Understanding of machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch
Experience with big data or lakehouse platforms such as Redshift, Snowflake, Databricks, Hadoop/Spark, or EMR
Experience in insurance or financial services, including familiarity with model validation and governance in regulated environments

Responsibilities

Contribute to the design, build, and support of a modern MLOps platform used across AI & Data teams
Design, implement, and operate secure, scalable DevOps and MLOps CI/CD workflows for data and ML applications and services
Develop and maintain on-premises and AWS-based data and ML infrastructure, including containerized training and inference and workflow orchestration (e.g., Airflow)
Partner with Technology (IT), SRE, and Security teams to integrate networking, identity, secrets management, and observability while ensuring compliance and governance
Serve as a platform subject matter expert by contributing to solution design, codifying best practices, and producing clear documentation and runbooks
Work both independently and collaboratively as part of an agile team
Support Scrum ceremonies by contributing to story creation, sprint planning, and sprint goals
Communicate technical concepts clearly and effectively to a diverse set of stakeholders
Stay current with emerging MLOps trends and technologies and identify opportunities to improve the platform and tooling