Senior Lead Software Engineer – AI

Thomson Reuters

Senior QA Software Engineer testing and validating AI-driven software systems at Thomson Reuters. Collaborating with cross-functional teams to ensure quality in AI solutions across legal and compliance domains.

Posted 6/23/2026full-timeBengaluru • 🇮🇳 IndiaSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaJUnitKubernetesOraclePythonSeleniumSQL

About the role

Key responsibilities & impact

Collaborate with a cross-functional team of product managers, UX designers, AI engineers, and software developers to design, implement, and execute comprehensive testing strategies for AI-powered solutions.
Design and implement comprehensive test strategies for advanced AI systems, including multi-component pipelines, retrieval-augmented generation (RAG), and custom AI agents with multi-step reasoning.
Develop automated testing frameworks for AI model performance, accuracy, and reliability in production environments.
Create test cases specific to AI/ML systems, including model validation, output quality assessment, and edge case testing.
Validate AI model integrations with production software through robust APIs and scalable data pipelines.
Test AI systems adapted to specialized domains, ensuring quality for expert systems in areas such as legal, tax, and compliance.
Evaluate and prototype cutting-edge testing techniques for AI systems to address unique quality challenges.
Mentor junior QA engineers and facilitate technical discussions on AI testing best practices.

Requirements

What you’ll need

Bachelor's degree in Computer Science or equivalent experience.
5+ years of experience in software quality assurance and test automation; at least 2 years focused on testing AI/ML systems.
70% automation/development experience, 30% manual testing experience.
Proficiency in Python and Java with strong coding skills for test automation.
Experience with test automation tools and frameworks (e.g., Selenium, pytest, JUnit).
Strong understanding of machine learning principles, evaluation metrics, and AI system testing methodologies.
Knowledge of MLOps/LLMOps and the end-to-end lifecycle of AI-powered software applications.
Experience testing AI model integrations in production systems using APIs and data pipelines.
Good knowledge and experience working with relational databases (SQL, Oracle) and ability to write complex SQL scripts.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization tools (e.g., Docker, Kubernetes).

Benefits

Comp & perks

Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role).
Flex My Way: A set of supportive workplace policies designed to help manage personal and professional responsibilities.
Career Development and Growth: Fostering a culture of continuous learning and skill development.
Industry Competitive Benefits: Comprehensive benefit plans to include flexible vacation, mental health days, access to wellness resources, etc.
Social Impact: Opportunities for paid volunteer days off and involvement in pro-bono consulting projects.

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Hard Skills & Tools

PythonJavatest automationautomated testing frameworksmodel validationoutput quality assessmentedge case testingSQLMLOpsAI system testing methodologies

Soft Skills

collaborationmentoringtechnical discussions

Certifications

Bachelor's degree in Computer Science