Senior Associate - Development Lead - Digital Experience Platform

New York Life Insurance Co•New York, NY

12d•Hybrid

About The Position

As part of Technology at New York Life, the Digital Experience Platform – Development Lead will drive the architecture, engineering strategy, and implementation of the next-generation Design-to-Dev and AI-enabled digital experience platform. This role will modernize how creative assets, UX/UI designs, content specifications, and AI-driven automation flow into production-ready digital experiences across the Adobe Experience Cloud and react-based front-end ecosystem. You will partner with product managers, designers, architects, MarTech leaders, AI engineers, and development squads to build a scalable, automation-first platform that transforms design artifacts and AI intelligence into reusable components, personalized journeys, and high-quality digital experiences. Your work will directly accelerate personalization, component reuse, operational efficiency, and time-to-market across the Client Prospecting value stream.

Requirements

Bachelor’s and/or master's degree in computer science, Engineering, AI, or related field.
Strong experience designing and delivering modern front-end architectures using: React (preferred), Angular or Flutter, Advanced HTML/CSS and component-based systems.
Hands-on experience building AWS-based front-end applications and cloud native deployments.
Working knowledge of Adobe Experience Manager (AEM) and its role in enterprise digital ecosystems.
Experience building scalable design systems, component libraries, and design-to-development automation workflows.
Demonstrated experience architecting automation solutions that transform UX/design artifacts into consumable code.
Experience building or deploying Agentic AI solutions within MarTech or digital experience platforms.
1+ year hands-on experience with AI orchestration frameworks such as LangChain, CrewAI, or similar.
Deep understanding of: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agent-based system design, Prompt management and AI guardrails.
Proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.
Knowledge of modern AI interoperability standards (e.g., MCP and emerging protocols).
Experience deploying AI/ML solutions in production environments using MLOps best practices.
7+ years of full-stack engineering experience (React, Java, Spring Boot, APIs).
Strong understanding of API-first and microservices-based architectures.
Ability to engineer complete systems across frontend, backend, infrastructure, and data layers.

Responsibilities

Architect and build the Digital Experience platform that converts design inputs and AI outputs into reusable, production-ready UI components.
Enable component orchestration across: React, Angular, Flutter, and modern HTML/CSS environments, Adobe Experience Manager (AEM Sites and Assets), AWS-hosted front-end applications.
Define reusable design systems, component libraries, and engineering standards across brands and digital properties.
Ensure support for multi-brand, multi-channel, and multi-device digital experiences.
Lead AI-first solution design across MarTech platforms including digital experience.
Architect agentic AI capabilities to automate: Design-to-code generation, Content creation and personalization, Component orchestration and optimization.
Implement LLM-based systems leveraging RAG, prompt orchestration, and agent frameworks (LangChain, CrewAI, or similar).
Integrate AI services with Adobe Experience Cloud, enterprise APIs, and AWS-based applications.
Establish guardrails for responsible AI, prompt governance, observability, and model evaluation.
Define engineering guardrails for accessibility (WCAG), performance, security, and scalable architecture.
Deploy AI and platform capabilities using cloud-native practices (AWS preferred).
Implement CI/CD automation, containerization, and MLOps patterns for AI-enabled services.
Ensure full-stack system integrity across front-end, backend, infrastructure, and data layers.
Reduce manual development effort through structured automation and reusable component patterns.
Partner with data and analytics teams to design retrieval pipelines and structured datasets for AI-driven personalization.
Lead development and optimization of ML/LLM models for digital marketing and experience use cases.
Ensure scalable integration of structured and unstructured data into personalization workflows.