Lead Full Stack Engineer

Voyager (94001), India, Bangalore, Karnataka

Lead Full Stack Engineer

At Capital One India, we work in a fast paced and intellectually rigorous environment to solve fundamental business problems at scale. Using advanced analytics, data science and machine learning, we derive valuable insights about product and process design, consumer behavior, regulatory and credit risk, and more from large volumes of data, and use it to build cutting edge patentable products that drive the business forward.

We are looking for a Lead Full Stack Engineer with strong expertise in Java or Python and Go, medium-level expertise in Javascript (Vue.js/React), and a deep understanding of AWS services. The ideal candidate should have experience working with open-source frameworks and a solid grasp of Machine Learning Observability. This role requires a hands-on leader who can drive technical excellence while collaborating with cross-functional teams to build scalable, high-performance applications.

The Machine Learning Experiences (MLX) team is at the forefront of how Capital One builds and deploys well-managed Machine Learning (ML) models and features. We onboard and educate associates on the ML platforms and products that the whole company uses. We drive innovation and research and we are working to seamlessly infuse ML into the fabric of the company. The ML experience we are creating today is the foundation that enables each of our businesses to deliver next-generation ML-driven products and services for our customers.

What You'll Do:

• Lead a portfolio of diverse technology projects and a team of developers with deep experience in large-scale full-stack systems, distributed microservices, and machine learning systems to create solutions that meet regulatory and business needs.
• Develop and maintain scalable full-stack applications using Java or Python, Go, and Javascript.
• Design and implement cloud-native solutions on AWS, leveraging services like Kubernetes and Serverless infrastructure.
• Work with open-source frameworks to accelerate development and optimize performance.
• Ensure high performance, security, and reliability of applications.
• Collaborate with ML engineers and data scientists to enhance ML observability and monitoring capabilities.
• Share your passion for staying on top of tech trends, experimenting with new technologies, participating in internal & external technology communities, and mentoring other engineers.
• Actively contribute to the codebase and evaluate code to maintain technical quality.
• Collaborate with digital product managers to deliver robust cloud-based solutions that drive powerful experiences to help millions achieve financial empowerment.
• Work with CI/CD pipelines, containerization (Docker, Kubernetes), and DevOps practices to improve deployment efficiency.
• Optimize backend performance and build robust APIs to support various business use cases.

• Bachelor's Degree
• At least 7 years of experience in software development, with a strong focus on backend and full-stack development.
• At least 5 years of expertise in Java or Python and Go, with the ability to design scalable and maintainable codebases.
• At least 5 years of experience in Javascript for frontend development.
• At least 5 years of experience with AWS services such as Lambda, ECS, EKS, S3, DynamoDB, SQS, IAM.
• At least 5 years of experience of open-source frameworks and their practical applications.
• At least 3 years of experience working on ML Observability tools and frameworks.

• Experience in monitoring ML models in production and integrating observability tools.
• Knowledge of event-driven architectures and microservices.
• Familiarity with GraphQL and WebSockets.
• Good understanding of CI/CD pipelines, containerization such as Docker, Kubernetes and DevOps practices.
• Strong understanding of data processing pipelines and streaming architectures.
• Strong problem-solving skills, attention to detail, and the ability to handle complex engineering challenges.
• Proven ability to work in agile environments and contribute to high-performance engineering teams.