Senior Associate - AI Engineer

Location: New York

Requisition ID93359

Department Tech Data AI Ventures Job Function Tech Data AI Ventures Location New  York,New York,United States Role Location Designation Hybrid - 3 days per week Location Designation:
Hybrid - 3 days per week

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.

What You’ll Do:

Contribute to the design, build, and support of a modern MLOps platform used across AI & Data teams

Design, implement, and operate secure, scalable Dev Ops 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

What You’ll Bring :6+ years of industry experience in software engineering, data engineering, Dev Ops, 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 Cloud Watch; familiarity with Sage Maker or similar platforms is a plus Solid understanding of CI/CD and Dev Sec Ops  best practices, including Git branching strategies, pull requests, code reviews, and artifact or security scanning (e.g., Jenkins, Git Hub Actions, Git Lab 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

Preferred

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

Pay Transparency Salary Range: $124,000-$177,000

Overtime eligible:
Exempt Discretionary bonus eligible:
Yes Sales bonus eligible:
No

Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an…