Available for select builds
I build dependable web products and the intelligent systems that make them feel remarkably human. My current edge is the space between a clean interface, a resilient backend, and an AI workflow you can actually observe and trust.
Pradeep
Full-stack developer / AI engineer in progress
“The best engineering is felt as clarity.”
06+
years building
24
systems shipped
∞
things to learn
01 / Delivery capabilities
Reader Realize is an MFE project that provides summaries of complete books, including a full page index and the assigned status for each student. Contributed to the Assignment module, which tracks whether a book or individual pages have been assigned and displays assignment details.
Resume module / delivery
Developed the Appysync project with Amplify. When a student interacts with an SCO, it triggers a GraphQL call to create or update the SCO, which then calls Resolver and pipeline functions.
Resume module / delivery
When content is ingested by the backend team, AWS SNS is triggered. Listened to SNS and processed the content further using AWS Step Functions.
Resume module / delivery
Built reusable components for various frameworks.
Resume module / delivery
Automated resource creation for different environments using CDK scripts with Node.js.
Resume module / delivery
Migrated old content to the new import workflow and transferred EFs to S3 using DataSync. Migrated student activity content using Python scripts and ECS.
Resume module / delivery
02 / The stack
The right tool is the one that makes the next decision clearer. Here’s the current working set.
AI implementation practice
Chunking, retrieval strategy, context assembly, grounded prompts, and citation-aware answers.
Planning, routing, tool selection, MCP contracts, state, and human approval for actions.
System prompts, structured outputs, few-shot examples, refusal behavior, and prompt versioning.
Golden datasets, relevance checks, faithfulness, latency, cost, and regression testing.
Ollama model serving, streaming responses, fallback behavior, and practical local development.
Prompt injection defense, secret isolation, access control, tool allowlists, and audit trails.
03 / Systems thinking
Two reference architectures from the workbench: a grounded Bedrock flow and an agent workflow with explicit boundaries around tools, data, and security.
Pattern A / modified RAG
Small modification: retrieval happens before Bedrock, then a response check adds citations and blocks unsupported claims.
Useful for: document Q&A, internal knowledge, and auditable assistant responses.
Pattern B / tool-using agent
Guardrails: authentication, authorization, input validation, tool allowlists, secrets isolation, and audit logs.
Useful for: operational assistants that can read, reason, and take controlled actions.
04 / The path
2022 — now
Product studio / independent
Designing and shipping high-traffic product surfaces, internal tooling, and integrations from first schema to deployed interface.
2020 — 22
SaaS platform
Built customer workflows with React and Node, improved API reliability, and helped a small team establish a pragmatic delivery rhythm.
2018 — 20
Digital products
Learned the craft through accessible, responsive experiences and a healthy obsession with the details users feel.
05 / Resume template
A structured view of the experience behind the systems. Ready to turn into a PDF resume when the final contact details are added.
Passionate Front-End Developer with 9 years of experience in Angular development and AWS cloud services.
Proficient in developing and managing dynamic, responsive, and user-centric web applications. Adept at leveraging modern frameworks and cloud solutions for efficient deployment, scaling, and management. Expertise in performance optimization, scalability, and DevOps principles. Strong collaborator and team player with a proven track record of delivering high-quality software solutions within agile environments, committed to achieving project goals through innovative and efficient coding practices.
Aug 2013 — Jul 2016
Front-end and cloud engineering work across learning platforms, content workflows, student activity, infrastructure, and migration programs.
Jul 2010 — 2013
Built a foundation across Windows and Linux environments, web application development, and collaborative delivery.
Selected delivery modules / Realize
Reader Realize is an MFE project that provides summaries of complete books, including a full page index and the assigned status for each student. Contributed to the Assignment module, which tracks whether a book or individual pages have been assigned and displays assignment details.
Developed the Appysync project with Amplify. When a student interacts with an SCO, it triggers a GraphQL call to create or update the SCO, which then calls Resolver and pipeline functions.
When content is ingested by the backend team, AWS SNS is triggered. Listened to SNS and processed the content further using AWS Step Functions.
Built reusable components for various frameworks.
Automated resource creation for different environments using CDK scripts with Node.js.
Migrated old content to the new import workflow and transferred EFs to S3 using DataSync. Migrated student activity content using Python scripts and ECS.
Technical toolkit
environments
Windows, Linux
frontend
Angular, JavaScript ES5/ES6, TypeScript, HTML5, CSS3, GraphQL, StencilJS, VTL
aws
SNS, SQS, S3, DynamoDB, Step Functions, Amplify, AWS AppSync, Batch, ECR, ECS, DataSync, EventBridge, API Gateway, Cognito, CloudWatch, Systems Manager
backend
Node.js, Python 3
database
DynamoDB, MySQL
infrastructure
CDK, CloudFormation
delivery
Docker, Git, GitHub, Jasmine, Jest