Top AI & Machine Learning Jobs

Design, build, and deploy cloud-native applications and platforms using AWS and GCP. Develop APIs, reusable services, automation, and agentic AI solutions while supporting generative AI applications. Apply infrastructure as code, containerization, DevSecOps, security, resilience, and performance standards. Collaborate with engineers, architects, data scientists, product teams, and business partners in an Agile environment, contributing to technical standards and architecture evolution.

Lead design and build of New York Life's enterprise AI platform and agentic solutions. Work across cloud-native infrastructure, model and agent lifecycle, RAG knowledge systems, multi-agent orchestration, MLOps/LLMOps, governance, CI/CD, observability, and production operations. Partner with security, legal, and architecture to embed responsible AI and deliver production-ready, compliant AI systems.

Leads end-to-end data science projects, including problem framing, data exploration, feature engineering, model development, evaluation, deployment, and communication. Applies statistical analysis, experimentation, and machine learning to business problems across marketing, underwriting, actuarial, operations, and fraud prevention. Partners with engineering and cross-functional stakeholders to deliver scalable analytical solutions, actionable insights, process improvements, and enhanced model performance.

Design and operationalize GenAI-enabled analytics to drive personalization, automation, and decision intelligence. Build and maintain scalable data models and pipelines (DBT, Databricks, Python/SQL). Lead prompt engineering and LLM fine-tuning, conduct feature attribution and ROI modeling, run advanced experiments, and deliver executive-level visual analytics and strategic recommendations across enterprise domains.

The Director of AI/Agentic Experience Strategy leads AI-driven customer lifecycle strategies, facilitates AI experience design, and collaborates across teams to enhance consumer interactions in financial services.

The Director of AI Search leads New York Life's AI Search strategy, overseeing AI acquisition strategies and driving AI innovation in marketing experiences. The role requires collaboration across functions to optimize content for AI discoverability and define future-state AI experiences while maintaining compliance and stakeholder alignment.

Lead New York Life’s enterprise AI governance function by building agentic governance solutions for security, risk, compliance, legal, and auditing across the AI lifecycle. Manage expert review teams, establish guardrails and control frameworks, oversee third-party AI governance, support regulatory examinations, and represent the organization with senior internal and external stakeholders. The role requires deep AI technology fluency, regulated-industry governance expertise, and executive-level leadership.

Leads New York Life’s AI Center of Excellence across frontier AI provider relationships, AI software lifecycle standards, platform architecture, governance integration, talent acquisition, upskilling, and production delivery. Builds and manages West Coast AI engineering teams, evaluates emerging AI technologies, establishes scalable governance and engineering practices, and owns measurable business outcomes from enterprise AI solutions. Provides senior leadership coverage for West Coast partners and coordinates with Home Office leadership.

Leads New York Life Direct’s AI enablement strategy, multidisciplinary team, and enterprise AI portfolio. Oversees agentic, generative, predictive, and machine learning solutions from discovery through production, monitoring, adoption, and optimization. Establishes architecture patterns, engineering practices, governance, responsible AI controls, evaluation frameworks, and success metrics. Partners with business, technology, security, data, cloud, and risk teams to deliver scalable AI capabilities and measurable business value while developing talent and driving organizational adoption.

Design and operationalize Python-based AI services, including LLM integrations, RAG, agent workflows, MCP, vector search, guardrails, and evaluation pipelines. Build a reusable enterprise AI and agent services layer, integrate with Java and other enterprise platforms, and develop secure data pipelines. Collaborate with engineering, compliance, legal, risk, and model governance stakeholders to ensure safe, auditable AI in a regulated insurance environment. Contribute to production-quality code, testing, CI/CD, observability, architecture reviews, and operational readiness.