Lead Software Engineer, AI Platform

apartmentThomson Reuters placeBangalore calendar_month 

Job Description

Job description

In this roleyou will help to develop, build, design, continuously improve, and support the AI Platform at Thomson Reuters. You will participate in all stages of development, use various software and tools, and enabling self-service tools for data science teams.

The role also involves designing, developing, integrating, and deploying tools for Data Science, GenAI and Machine Learning (ML) Research.

The successful applicant will design and operate a framework for Machine Learning Operations (MLOps), advise on software engineering for ML, and ensure consistency with cloud architectural principles.

The role requires continuous evolution of the platform and keeping up to date with new technologies.

Applicants should have 7 years of software engineering experience, hands-on experience with a public cloud technology (AWS, Azure, or GCP), experience with service-oriented programing and design, microservices architecture, and serverless application model.

A good candidate should have good experience with LLMs and GenAI, AWS SageMaker, Azure ML or similar Cloud AI capabilities.

Proficiency in modern programming languages such as Python, JavaScript, TypeScript is required, while also being comfortable developing with other languages such C/C++, Java,Rust, and Go.

Have experience with relational and non-relational databases, integration, and Agile development methodologies.

DevOps experience and an understanding of frontend development are also important.

The role requires technical leadership and a positive attitude.

About the Role:

In this opportunity as a Lead Software Engineer, BI Platform, you will:

  • Build and evolve the AI Platform which includes being able to assess the current architecture and map to the target state.
  • Participate in all aspects of the development lifecycle: Ideation, Design, Build, Test and Operate
  • Utilize a variety of software and tools both commercial and open source.
  • Enable self-service tooling for data science teams to create and maintain models.
  • Design, develop, integrate, and deploy tools for Data Science, GenAI and ML Research, such as, Model Monitoring, Model Governance, Model Deployment, Data Management, Feature Engineering, among others.
  • Be able to design, implement, and operate a framework for Machine Learning Operations (MLOps). Design, evaluate, and advise on the day-to-day work of Software Engineering for Machine Learning
  • Ensure consistency with cloud architectural guiding principles.
  • Continuously challenge and evolve the existing platform capabilities and keep up to date with new offerings.

About You

You are a fit for the role of Lead Software Engineer, AI Platform, if you meet all or most of these criteria:

  • 7 years experience in Software Engineering
  • Hands-on experience working with at least one public cloud technology (AWS, Azure)
  • Experience with service-oriented and/or microservices architecture
  • Experience with LLMs and GenAI, AWS SageMaker, Azure ML, or similar Cloud AI capabilities
  • Proficiency in modern programming languages such as Python, JavaScript, TypeScript, C/C++, Java.
  • Experience with relational and non-relational databases
  • Experience with Agile development and delivery Scrum, Lean, XP, Kanban methodologies.
  • Hands on DevOps experience CI/CD in AWS, Git, GitHub, Monitoring, Log Analytics and others.
  • A good understanding of frontend development (UI/UX concepts and frameworks, HTML, CSS, and Javascript) is an asset and a strong differential for this role.
  • Technical leadership including being able to break down high level requirements to features
  • A can do attitude,with a great sense of ownership and teamwork.
  • Ability to develop prototypes, showcase new functionalities to the rest of the team, demonstrateimplementation patterns, advise, and guide other team members.
  • Ability to find problemsand chase, then lead the team to solve them end to end.
  • Ability to thrive in global teams with peers in different timezones
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