Principal AI Engineer

Principal AI Engineer

Location Designation:
Hybrid - 3 days per week

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.

As a Principal AI Engineer within the Artificial Intelligence & Data (AI&D) organization, you will serve as a senior technical leader responsible for designing, building, and delivering enterprise AI solutions that create measurable business value. This is a hands-on engineering role that spans traditional machine learning, Generative AI, and Agentic AI, requiring deep technical expertise across the full AI solution lifecycle—from opportunity assessment and solution architecture through deployment, monitoring, and continuous improvement.

Working closely with business stakeholders, product managers, data scientists, software engineers, and technology partners, you will lead the delivery of production-ready AI solutions on New York Life's enterprise AI platform. Rather than developing the underlying platform infrastructure, you will leverage enterprise capabilities to rapidly deliver scalable, secure, and responsible AI applications that solve complex business problems.

In addition to leading technical delivery, you will help define AI engineering standards, influence enterprise AI strategy, mentor engineers, and partner with the business to measure and maximize the value generated by AI investments.

· Lead the end-to-end delivery of AI and Generative AI solutions, partnering with business, product, technology, and data teams to identify opportunities, shape solution strategies, and deliver measurable business outcomes.

· Design, develop, deploy, and operate production AI applications using the enterprise AI platform, leveraging existing CI/CD pipelines, infrastructure templates, security controls, and platform services.

· Architect and implement advanced AI solutions, including agentic AI systems, multi-agent orchestration, retrieval-augmented generation (RAG), hybrid retrieval strategies, and human-in-the-loop workflows to address complex business challenges.

· Evaluate, select, and integrate AI technologies across the solution stack, including foundation models, orchestration frameworks, cloud AI services, and modern software engineering tools, ensuring solutions are scalable, secure, and maintainable.

· Establish engineering best practices for AI development, including evaluation frameworks, automated testing, observability, responsible AI, safety validation, and production monitoring.

· Rapidly prototype AI-enabled applications and user experiences to validate concepts, accelerate adoption, and inform product direction using modern development frameworks.

· Leverage AI-assisted software development tools to accelerate engineering productivity while maintaining high standards for code quality, testing, and governance. Develop internal engineering agents that improve software delivery through automation of testing, code review, deployment validation, and other engineering workflows.

· Provide technical leadership, mentorship, and architectural guidance to AI engineers and data scientists, fostering a culture of innovation, experimentation, technical excellence, and continuous learning.

· Partner with business leaders to define success metrics, measure solution performance, and continuously optimize AI solutions to maximize business value.

· Stay current on emerging AI technologies, evaluate their applicability to enterprise use cases, and influence the organization's AI roadmap…