Team Lead - Software Engineering

Team Lead - Software Engineering

We are seeking a highly experienced and future-focused Team Lead to lead the development of our next generation of cloud-native, scalable AI-powered applications.

This role is ideal for a seasoned Software Engineer with a deep background in delivering robust, high-performance software systems who is ready to pivot their expertise to the AI/ML application space. You will act as the critical bridge between data science innovation and production-ready software, ensuring that all Data Science solutions are delivered as seamless, resilient, and highly available applications.

You will leverage your extensive experience to design systems from scratch, manage complex stakeholder relationships, and mentor a growing team dedicated to the future of AI in our products.

 

About You (Skills & Qualification Required)

• Must have a bachelor’s degree in Engineering or master’s degree (BE, ME, B Tech, M Tech, MCA, MS)

• Minimum 7 years of experience developing web-based applications using Java, Spring, Hibernate, MS SQL Server, and related technologies.
• Exposure to team management
• Exposure to Cloud native technologies and integration patterns
• Experience in writing Unit test cases
• Good understanding of software development principles, including Distributed System, object-oriented programming, Design Patterns, and SOLID principles.
• Working knowledge of VCNs e.g., GIT, SVN etc.
• Experience with AWS services, such as EC2, S3, and RDS   
• Experience with Agile development methodologies
• Experience with front-end web technologies such as HTML, CSS, JavaScript, and Angular

 

It would be great if you also have,

• Prior experience successfully launching and scaling Java based application
• Exposure to in modern DevOps, CI/CD pipelines, and infrastructure-as-code principles.
• Experience with real-time data processing and streaming technologies (e.g., Kafka).
• Exposure to Docker, and Linux .

 

 

What will you be doing in this role? 

• System Design & Architecture: Lead the end-to-end design, development, and deployment of applications and features, ensuring they are scalable, highly available, and cloud native.
• Stakeholder Management: Serve as the primary technical point of contact for product management, data science, and executive stakeholders, aligning technical priorities with overall business goals.
• Requirements Definition: Lead the gathering, documentation, and technical translation of both functional and non-functional requirements (e.g., performance, security, cost, scalability) for AI applications.
• Team Leadership: Provide people management, mentorship, and technical guidance to the engineering team, fostering a culture of technical excellence, accountability, and continuous improvement.

 

About the Team   

This person will lead the team building and managing one of the core Trademark Application. Our core application stack is cloud-native and includes technologies like Java/Python and Angular, leveraging AWS infrastructure, and utilizing both NoSQL and SQL databases for persistence.

In the AI domain, we use a hybrid approach to model deployment and consumption, including integration with the Azure OpenAI API and deploying our own internally self-hosted LLMs (Large Language Models) that we train for specific tasks. Our MLOps pipeline relies on SageMaker for robust model training and deployment, MLFlow for experiment tracking and model registry, and various specialized LLM observability tools to monitor performance, drift, and responsible usage in production.

Hours of Work

The role and employment will be of fulltime with Clarivate. You will be working in IST time zone. 9 hours of work per day including 1-hour lunch break.

 

At Clarivate, we are committed to providing equal employment opportunities for all  qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.

Experience Level

Senior Level