What you will do:   

• Architect, design and deliver high-quality code by promoting and defining INDG best practices.  

• Serve as a strong influencer on technical trends across multiple areas. 

• Deliver and present solutions for large initiatives across multiple verticals. 

• Design, develop scalable, high availability, high performance products with a deep understanding of front end and back-end architectures. 

• Shape broad architecture; ships multiple large services, complex libraries, or major pieces of infrastructure. 

• Identify technology and AI-driven strategic growth opportunities that enable INDG to expand product capabilities and operational efficiency.

• Lead cross team efforts and projects that span multiple domains and business units. 

• Participate in providing technology roadmap/vision for the team. 

• Collaborate with cross-functional teams and communicate technical solutions to non-technical people across the organization. 

• Participate in special projects and performs other duties as assigned.  

• Architect and scale AI/ML systems across products, including real-time and batch inference on AWS, while implementing MLOps best practices for model lifecycle management, monitoring, evaluation, drift detection, and reliable data engineering pipelines.

• Drive cross-team adoption of AI-driven automation within core product workflows.

• Lead adoption of AI-augmented software engineering by integrating coding assistants into development workflows, establishing safe-use standards, and continuously improving team productivity through AI tooling.

You need to have:  

• Bachelor’s degree in related field or equivalent experience. 

• 7 years of software development experience and/or commensurate skills building commercial applications with modern software engineering principles and practices.  

• Knowledge across multiple technical domains and an understanding of how and why technologies are deployed and utilized at INDG. 

• A track record of building stability, performance, and scalability across major business-critical systems. 

• A clear understanding of the relationship between complexity and cost and a record of successfully devising and implementing long-term strategies to lower it. 

• Demonstrated experience of cloud technologies i.e. AWS, Serverless, Event Driven Architecture, SOA, MicroServices, Microfrontend, CI/CD, Infrastructure as code, and other modern technologies. 

• Demonstrated experience of professional software engineering practices and the full software development life cycle, including coding standards, architecture/design patterns, code reviews, source control management, build processes, testing, and operations. 

• Strong data engineering skills, including building and maintaining scalable data pipelines, designing reliable data models, and optimizing data processing workflows in cloud-based environments

• Experience designing, deploying, and integrating ML systems or AI-enabled applications, including LLM and retrieval-based solutions, in production environments, with the ability to design scalable model-serving infrastructure and evaluate tradeoffs across accuracy, latency, cost, and maintainability.

• Strong understanding of the end-to-end ML lifecycle, from data preparation and training to deployment and monitoring, with familiarity in MLOps and CI/CD for models

• Proficient in using AI-powered coding agents throughout the software development lifecycle, effectively combining human architectural judgment with AI-assisted implementation to accelerate delivery while maintaining quality.