Senior Full-Stack AI Engineer for Data & Analytics

LSEG (London Stock Exchange Group); New York (NY); On-site; USD 113,900 - 189,900; Full time

Benefits offered by this job

Annual Incentive Plan

Medical, Dental, Vision

401(k) Savings Plan and Company match

Wellness Allowance

Job summary

LSEG Data & Analytics is seeking a Senior Associate Full Stack Developer with AI expertise in New York. The role focuses on designing, developing, and delivering end-to-end solutions that blend robust full stack engineering with applied AI capabilities to drive insights and value across the organization.

Responsibilities include building dashboards, APIs, and data layers, ensuring performance and security, and leveraging MCP tools and AI frameworks within cloud environments.

Qualifications

• Experience designing and building end-to-end full-stack solutions with integrated AI capabilities.
• Ability to work with Azure/AWS and containerized environments.
• Strong communication and documentation skills to convey complex concepts.

Responsibilities

• Develop and integrate end-to-end full-stack solutions across frontend, backend, APIs, and data layers.
• Build user-facing dashboards, interfaces, and APIs, including those powering AI-driven applications.
• Ensure high performance, security, and scalability of applications.
• Work with modern frameworks, cloud platforms (Azure/AWS), and containerized environments.
• Apply working knowledge of AI/ML concepts, models, and pipelines to support development efforts.
• Build and experiment with AI/ML components, integrating them into existing systems and workflows.

Skills

Full stack development

AI/ML concepts

Cloud platforms (Azure/AWS)

APIs

Containerization

Communication

Tools

MCP tools

AI frameworks

REST APIs

Job description

LSEG Data & Analytics is seeking a Senior Associate Full Stack Developer with AI expertise in New York. The role focuses on designing, developing, and delivering end-to-end solutions that blend robust full stack engineering with applied AI capabilities to drive insights and value across the organization.

Responsibilities include building dashboards, APIs, and data layers, ensuring performance and security, and leveraging MCP tools and AI frameworks within cloud environments.