Experience

I’m a software engineer working across backend systems, cloud infrastructure, and AI applications. My work has grown from full-stack product development into deployment automation, operations, and AI-enabled support systems.

Professional experience

StockDaddy

Senior Software Engineer · November 2021–present

StockDaddy is a trading education platform. My responsibilities span application development, payments and access workflows, AWS infrastructure, deployment pipelines, and AI applications.

Cloud and DevOps

I’ve taken on DevOps work alongside application engineering for several years. My responsibilities include operating containerized services on AWS, maintaining deployment pipelines, and troubleshooting infrastructure and application issues.

• Work with AWS services including ECS, Lambda, EC2, S3, ECR, RDS, VPC, CloudWatch, and CloudFront.
• Build and maintain GitHub Actions pipelines for application delivery across environments.
• Work with Docker packaging, configuration, access permissions, and deployment checks.
• Investigate failures using application logs and infrastructure signals, with attention to safe recovery.

AI applications

I’ve built a chatbot and support agent using retrieval-augmented generation to bring relevant information into responses.

• Added tools that retrieve real-time information during conversations.
• Used evaluations to assess responses and agent behavior.
• Integrated Langfuse for observability and investigation.
• Added guardrails to constrain application behavior.
• Handle MLOps responsibilities alongside AI application development, while continuing to deepen my understanding of model lifecycle practices.

Backend and application systems

My backend work includes APIs, payment processing, administrative tools, and the data workflows behind them.

• Build and maintain services using Node.js, NestJS, TypeScript, and REST APIs.
• Work on Razorpay integrations, webhook handling, retries, payment verification, and order state.
• Maintain enrollment and access workflows, coupon validation, authentication, and role-based access control.
• Work with PostgreSQL and Redis for application data, caching, and sessions.
• Build internal dashboards and operational tools with React and Next.js.

Mu Sigma

Decision Scientist · January 2021–October 2021

Worked on statistical modeling, feature engineering, exploratory analysis, and automated data pipelines using Python and SQL. The work involved Pandas, NumPy, and Scikit-Learn for analysis and modeling.

Vijayshree Group

Full-Stack Developer · June 2019–February 2020

Developed web platforms and booking systems using Node.js and React, with deployment work on AWS EC2, S3, and Route53. Responsibilities included server configuration, SSL setup, and SEO-related improvements.

Ongoing learning

Since May 2026, I’ve been studying AI application development more systematically alongside my professional responsibilities.

• Agent systems: tool design, memory, orchestration, MCP, and A2A.
• AI application quality: evaluation datasets, response checks, observability, and guardrails.
• MLOps and model lifecycle: model versioning, validation, deployment, monitoring, and reproducibility. Tools I’m exploring include MLflow, DVC, Feast, KServe, Great Expectations, and SageMaker AI.
• Cloud operations: continuing to improve my understanding of infrastructure as code, deployment safety, and recovery.

My personal projects document separate experiments and case studies. They are kept outside this employment history.

Core tools and practices

• Backend: Node.js, NestJS, TypeScript, JavaScript, Python, SQL, REST APIs, and webhooks.
• Cloud and delivery: AWS, Docker, GitHub Actions, Terraform, and CloudWatch.
• AI applications: RAG, tool calling, evaluations, Langfuse, and guardrails.
• Data and interfaces: PostgreSQL, Redis, React, and Next.js.