Senior Lead Software Engineer – Python, Data, Cloud, AIML

Overview

You will drive end-to-end software development in a Cloud-native, data- and AI-enabled environment within Markets Research Technology. As a senior individual contributor and leader, you design scalable solutions, oversee secure production code and architecture, and industrialize AI/ML at production scale. You collaborate with cross-functional teams to deliver trusted market-leading tech aligned with the firm’s objectives. This role offers hands-on engineering, with opportunities to shape data pipelines, ML workflows, and governance practices at scale.

Responsibilities

• Deliver software solutions and tackle complex problems beyond routine approaches
• Create secure, high-quality production code and maintain production-ready algorithms
• Produce architecture and design artifacts for complex applications and ensure design constraints are met
• Build the data and AIML engineering stack, including data engineering, backend, cloud infrastructure DevOps, and MLOps
• Design and implement data engineering solutions using modern big data technologies
• Drive adoption and governance of AI-assisted engineering practices across teams with measurable quality and security standards
• Leverage SDLC tools and AI-assisted development and automation capabilities to improve value at scale
• Contribute to engineering communities of practice and stay engaged with emerging technologies
• Demonstrate a passion for learning, problem-solving, and a can-do attitude

Key requirements

• Formal training or certification in software engineering concepts
• Hands-on system design, application development, testing, and operational stability
• Proficiency in Python and experience with one or more modern programming languages
• Experience in large corporate environments and knowledge of the Software Development Life Cycle
• Proven track record in microservices, distributed systems, and data-intensive applications
• Experience with Cloud services, Infrastructure as Code, containerized development, big data, and modern data engineering
• Practical experience delivering production-scale cloud-native data engineering solutions
• Familiarity with Cloud Data engineering services (ETL, Glue, S3, Athena) and MLOps stack
• Experience leading the use of enterprise AI-assisted development tools and setting expectations for AI outputs
• Strong understanding of responsible AI, data sensitivity, security, and resiliency

• clear communication with stakeholders across backgrounds
• problem-solving and creative thinking
• collaborative mindset
• Python
• microservices
• distributed systems

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