Senior Associate - AI Engineer

Location Designation: Hybrid - 3 days per week Technology, Data, AI and Ventures: Within the Tech, Data, AI, Ventures (TDAV) organization, our work is guided by a shared vision: deploying the power of technology, data, AI and ventures to accelerate sustainable competitive advantage for New York Life's businesses. We build solutions that power how we serve policy owners, agents, advisors and employees while delivering measurable business outcomes. Across technology, data, AI, cyber, product, digital experience, architecture and infrastructure, TDAV combines the scale and investment of an industry leader, access to leading-edge technologies and the opportunity to help shape how a world-class financial services company competes in the AI era - all backed by the stability and purpose of a mutual company built to last. Role Overview As part of the Artificial Intelligence & Data (AI&D) organization, you will contribute to New York Life's digital transformation by developing and deploying AI and machine learning solutions that enhance efficiency and improve client, agent, and employee experiences. This role will support the development of AI solutions, spanning traditional Machine Learning, Generative AI, and Agentic AI. The role focuses on building core technical skills, learning enterprise AI practices, and delivering well-defined components of AI solutions. You will collaborate closely with Data Scientists, Engineers, and product and technology partners while developing an understanding of model lifecycle management, responsible AI principles, and New York Life's technology ecosystem. What You'll Do • Execute AI/ML initiatives in partnership with data, technology, product and business teams. • Deliver business-aligned OKRs, ensuring AI initiatives are outcome-driven and tied to enterprise value creation. • Contribute to the end-to-end model lifecycle: data exploration, feature engineering, model training/validation, deployment, monitoring, and iteration. • Design, build, and validate ML models across supervised and unsupervised paradigms (e.g., classification, regression, survival analysis, clustering), with attention to model selection, evaluation strategies, and production-readiness. • Apply statistical methods and experimentation techniques — including hypothesis testing, causal inference, and A/B testing — to validate model performance and drive evidence-based decisions. • Develop and help operationalize models using AWS/GCP (e.g., SageMaker, Bedrock) and modern data platforms (Snowflake, Databricks), ensuring quality, security, and scalability; partner with ML engineers for large-scale production deployment and scaling. • Assist in designing and evaluating agentic/AI-powered solutions that automate routine business tasks with human-in-the-loop checkpoints, escalation thresholds, and safety guardrails. • Assist in implementing and refining LLM/RAG approaches (vector stores, embeddings, retrieval optimization, prompt orchestration) with evaluators for reliability. • Ensure AI capabilities are accessible through APIs, dashboards, and integrated workflow applications used by business teams. • Build lightweight UI prototypes (e.g., Streamlit) to validate usability and support adoption. • Adhere to model governance, documentation, testing, and CI/CD best practices in partnership with MLOps. What You'll Bring • Advanced degree in Computer Science, Data Science, Machine Learning, AI, Engineering, Mathematics, Statistics, or a related quantitative field. • 3+ years of hands-on experience building and deploying ML models to solve real-world business problems, including feature engineering, model selection, validation strategies, and performance monitoring. • Strong foundation in statistics and machine learning — including supervised/unsupervised methods, probabilistic modeling, and model interpretability (e.g., SHAP) — with the ability to select and evaluate appropriate approaches for a given problem. • Proficiency in Python and SQL; working knowledge of core software engineering concepts (version control with Git/GitHub), testing and documentation. • Working knowledge of Generative AI concepts (e.g., LLMs, prompt engineering, RAG). • Exposure to Agentic AI architectures (e.g., tool-using agents, orchestration frameworks). • Ability to partner with business stakeholders and communicate model design and outcomes to both technical and non-technical audiences. • Strong communication skills and a collaborative mindset. • Proactive mindset and commitment to continuous learning. • Experience in the Life Insurance industry or consumer finance domains is a plus. Job Level: LEVELPF3 Pay Transparency Salary Range: $100,000-$143,000 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 annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program. Company Overview At New York Life, our 180-year legacy of purpose and integrity fuels our future. As we evolve into a more technology-, data-, and AI-enabled organization, we remain grounded in the values that drive lasting impact. Our diverse business portfolio creates opportunities to make a difference across industries and communities—inviting bold thinking, collaborative problem-solving, and purpose-driven innovation. Here, you’ll find the rare balance of long-standing stability and forward momentum, supported by an inclusive team that honors tradition while embracing progress. As a Fortune 100 mutual company, we offer a place to grow your skills, contribute to meaningful work, and deliver solutions that matter. Your ideas drive what’s next, and your growth powers it. Our Benefits We provide a full package of benefits for employees – an