Top AI & Machine Learning Jobs

Design, build, and deploy cloud-native, agentic AI applications on AWS/GCP. Apply AI and automation to improve developer productivity, design and consume APIs, ensure security and compliance, support generative/agentic AI in production, collaborate in Agile teams, and contribute to architecture and engineering best practices.

Lead the engineering and enterprise adoption of IAM orchestration and MCP gateway capabilities while building New York Life’s governed cyber multi-agent ecosystem. Design production AI agents, RAG architectures, agent registries, identity-aware APIs, and policy enforcement on GCP and AWS. Secure autonomous workflows against prompt injection and privilege escalation, oversee IAM integrations, mentor technical teams, and represent the CISO organization on AI security review boards.

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.

The Director will strategize and govern AI experiences for field personas, develop frameworks, conduct hands-on AI concept experimentation, and ensure alignment across stakeholders.

This role involves leading data science projects, developing machine learning models, collaborating with stakeholders, and mentoring other data scientists.

Lead design and delivery of full‑stack, cloud‑native AI and GenAI solutions; define AI strategies; architect secure, scalable platforms; mentor engineering teams; run pilots, integrate successful technologies, and partner across cloud, security, data, and business stakeholders to improve developer experience and drive enterprise adoption.

Design, build, and operate secure, compliant, scalable GCP cloud and AI platforms. Provide IaC (Terraform), GKE/container orchestration, Vertex AI/GenAI enablement, CI/CD and MLOps foundations, security and governance controls, observability, cost optimization, and cross-team collaboration to support AI workloads in a regulated financial environment.

Own end-to-end decision intelligence product domains: build, deploy, and monitor ML models and behavioral signals; lead experimentation and causal measurement; develop generative AI solutions and personalization; partner with product and engineering to define roadmaps and reusable ML platform assets that drive measurable business outcomes.

The AI Solution Architect designs enterprise architectures for AI solutions, ensuring they align with business objectives and technology standards while guiding implementation and governance.