Senior Associate - AI & Data Engineering

As part of the AI & Data Engineering group, you will build internal and customer-facing AI focused web applications for monitoring, onboarding, workflow management, and reporting across LSEG's real-time data and delivery estate.

Key Responsibilities

• Design and deliver scalable AI enabled backend services, RESTful APIs, microservices, data pipelines, and reporting solutions using Java (Spring Boot) and Python.
• Act as the technical lead for a sprint team or squad, guiding solution design, technical decisions, estimation, delivery, and resolution of engineering blockers.
• Lead Agile ceremonies, including refinement, sprint planning, daily stand-ups, reviews, retrospectives, and delivery tracking.
• Collaborate with interested parties, Business Analysts, Product Owners, QA, and engineering teams to shape requirements and deliver practical solutions.
• Mentor engineers through design discussions, code reviews, solving, knowledge Transfer, and engineering guidance.
• Drive engineering quality across automated testing, CI/CD, observability, security, code quality, documentation, and production support.
• Ensure solutions meet performance, scalability, reliability, security, and maintainability requirements.
• Champion responsible use of AI-assisted development to improve engineering quality, productivity, and team capability.

Required Skills & Experience

• 7+ years of professional software engineering experience, with strong hands-on backend development and technical leadership experience.
• Strong expertise in Java (Spring Boot), with good working knowledge of Python.
• Experience designing, building, integrating, and supporting RESTful APIs, microservices, and distributed systems.
• Strong SQL and relational database experience (PostgreSQL or similar), with exposure to Snowflake or other cloud data warehouse technologies.
• Experience making pragmatic architecture and design decisions, assessing technical trade-offs, and translating requirements into maintainable solutions.
• Experience leading technical delivery for a squad or small team while remaining hands-on with development.
• Experience with automated testing, Git, CI/CD pipelines, code quality practices, and modern software delivery processes.
• Hands-on experience with AWS, Docker, Kubernetes, and event-driven architecture using Kafka, Redis, or similar technologies.
• Experience solving production systems using logs, monitoring, metrics, tracing, and debugging tools, with a methodical approach to root cause analysis.
• Strong understanding of secure coding, common application vulnerabilities, authentication, authorization, and operational risk.
• Strong communication, mentoring, interested party engagement, and problem-solving skills.
• Hands-on experience with AI-assisted development, prompt and context engineering, LLM APIs, AI agents, MCP, and RAG-based solutions, with a responsible approach to correctness, security, privacy, and maintainability.

What Success Looks Like

• Provides clear technical direction while continuing to contribute hands-on to delivery.
• Helps the squad effectively, resolve blockers, and deliver reliable solutions in manageable increments.
• Raises engineering standards through mentoring, reviews, automation, observability, and continuous improvement.
• Builds trusted relationships with interested parties and turns business needs into practical technical outcomes.
• Helps maintain secure, scalable, resilient, and well-documented systems.