Abhishek Reddy Boddu
Python Backend & Applied AI Engineer
Former Amazon SDE I building production-grade FastAPI backends, orchestrating multi-agent workflows with LangGraph, deploying high-accuracy RAG vectors, and designing serverless AWS pipelines.
AWS & PIPELINES
Serverless ETL, Lambdas, SQS/SNS, S3 data handoffs, Step Functions.
APPLIED AI SYSTEM
LangGraph DAG topologies, pgvector similarity query, guardrails, evaluations.
01 / Python & FastAPI Backends
Building type-safe API gateways, high-throughput workers, pgvector indexes, and structured database layouts.
02 / Applied AI topologies
Deploying multi-agent LangGraph workflows, high-precision RAG context retrieval, prompt safety shields, and human-in-the-loop validation.
03 / AWS Cloud Infrastructure
Orchestrating serverless Lambda ETL jobs, Step Functions state machines, SQS queues, and S3-based handoff pipelines.
01 / Profile
Engineering dashboard & impact stats
Amazon backend scale meets practical AI automation.
I'm Abhishek (Abhi). My focus is writing clean, predictable Python backend logic, building robust microservices, and integrating agent workflows where they actually solve user issues.
At Amazon, I learned that correctness, instrumentation, and failing gracefully are far more important than bleeding-edge buzzwords. Recently, I've translated that mindset to LangGraph workflow graphs, security guardrails, and RAG databases.
Focused Toolkit
Tools I use to build scalable APIs and AI pipelines.
Amazon Production Work
HR Request APIs
React, FastAPI, and AWS-backed services for HR requests.
Self-Provisioning
Time-capture self-service kiosks across tablet/mobile platform.
Lambda ETLs
Python ETL pipelines using Step Functions and S3 handoffs.
GitHub Activity
02 / Capabilities
What I can ship
The center of gravity is backend reliability with modern product surfaces and AI workflows where they actually help.
Backend APIs
FastAPI services, database-backed workflows, clean service boundaries, validation, migrations, and observable request paths.
Applied AI Workflows
LangGraph agents with RAG, tool calling, durable memory, evals, streaming UX, and human approval gates around sensitive actions.
Production Readiness
Failure-first engineering: retries, idempotency, guardrails, rate limits, security headers, SEO, and deployment-friendly structure.
03 / Projects
Work that proves the engineering
A tighter project set: one flagship AI/backend system, one live production-facing site, and one exploratory agentic workflow.
Flagship applied AI/backend project
AbhiMart AI Customer Support Agent
Production-style support backend using FastAPI, LangGraph, PostgreSQL/pgvector, Gemini, RAG, SSE streaming, durable memory, evals, observability, guardrails, and HITL refund approval.
Tool-based order/product lookup with RAG over policy documents
LangSmith/local evals, OpenTelemetry/Jaeger, and Prometheus-style metrics
Prompt injection, PII, cross-customer access, and refund safety guardrails
Live client-style Next.js project
aicloudhub.com
Migrated and built a production-facing AI consulting site with Next.js App Router, Sanity CMS, ISR, Vercel deployment, Redis rate limiting, Zod validation, SEO metadata, sitemap generation, and security headers.
Improved Lighthouse/page-load latency by about 30%
Dynamic CMS routes with ISR instead of fully dynamic rendering
Contact/application protection through validation and rate limiting
Agentic workflow prototype
Personal OS
Conversational life-management assistant exploring multi-intent routing, parallel LangGraph fan-out, typed UI messages, and interrupt-driven confirmation before database writes.
Natural-language finance, journal, and media logging
Human confirmation before higher-risk writes
React UI cards rendered from graph outputs
Honest scope: AbhiMart and Personal OS are hands-on production-style portfolio projects, not company production deployments. Real production experience comes from Amazon and aicloudhub is live client-style work.
04 / FAQ
Frequently Asked Questions
Quick insights into my backend engineering philosophy, agent workflows, and cloud patterns.