5+ Years Production EngineeringFull-Stack • Cloud • MLOpsAWS & Reliability

Experience

I am a software engineer with **5+ years of experience** building and operating production systems. My career began in full-stack product engineering and has evolved into backend architecture, serverless GenAI pipelines, AWS cloud infrastructure, and MLOps.

Work History

StockDaddy

EdTech / FinTech

Senior Software Engineer / Full-Stack Engineer

Nov 2021 – Present

StockDaddy is a trading education platform operating large-scale backend systems for course delivery, payments, and operational workflows. My role bridges application engineering and infrastructure operations, managing the entire lifecycle of production services.

LLMOps & Generative AI
  • • Serverless Agentic RAG microservice with AWS Bedrock (Claude 3 Haiku, Titan Text v2) on AWS Lambda.
  • pgvector (PostgreSQL with HNSW indexing) for semantic policy search, deterministic tool-calling, and pre/post-flight regulatory guardrails.
Backend & Modular Architecture
  • • High-performance services in Node.js, NestJS, TypeScript, and REST APIs.
  • • Modular service boundaries, robust validation schemas, and role-based access control (RBAC).
Payment & Transaction Integrity
  • • High-reliability Razorpay webhook processing with idempotent retry logic.
  • • Automated course enrollment workflows, coupon validation, and transactional consistency.
Cloud Infrastructure & CI/CD
  • • Operated containerized workloads on AWS (ECS, Lambda, S3, ECR, RDS, CloudFront, VPC).
  • • Designed automated GitHub Actions pipelines for multi-environment deployments.

Mu Sigma

Decision Scientist

Jan 2021 – Oct 2021

Developed analytical systems, statistical modeling, and automated data pipelines to drive business intelligence:

  • • Applied statistical modeling, feature engineering, and exploratory analysis for enterprise decision frameworks.
  • • Built automated data pipelines using Python, Scikit-Learn, Pandas, NumPy, and SQL.

Vijayshree Group

Full-Stack Developer

Jun 2019 – Feb 2020

Developed and deployed customer-facing web platforms and booking systems on AWS infrastructure (EC2, S3, Route53, Node.js, and React).

The Transition to Cloud, Reliability & MLOps

Operating production systems exposed the critical importance of deployment safety, feature reproducibility, and infrastructure efficiency. With roots in data science and full-stack engineering, my focus centers on:

MLOps & Model Lifecycle: MLflow, Feast, DVC, KServe, SageMaker AI
Generative AI & LLMOps: AWS Bedrock, Claude 3, pgvector, Guardrails
Cloud Infrastructure: AWS ECS Fargate, Lambda, VPC, IAM, CloudWatch
Deployment Safety: GitHub Actions CI/CD/CT, Multi-Arch Docker

Technical Skills Summary

MLOps & Generative AI

MLflowDVCFeast Feature StoreKServeSageMaker AIAWS BedrockClaude 3pgvector (HNSW)Great ExpectationsEvidently AI

Languages & Backend

Python 3.11TypeScriptJavaScriptFastAPINode.jsNestJSExpressREST APIsWebhooksSQLRBAC / Auth

Cloud & DevOps

AWS ECS FargateAWS LambdaAmazon API GatewayDocker (Multi-Arch)GitHub Actions CI/CDTerraformAmazon ECRAWS S3Amazon RDSAmazon CloudWatchVPC Networking

Databases & Storage

PostgreSQLpgvectorRedisMongoDBAWS S3Parquet

Frontend & UI

ReactNext.jsTypeScriptTailwindCSS