I help engineering teams close the gap between “it works on my machine” and “we can trust it with real users, real load, and a real bill.”
For CTOs, founders, and platform teams facing rising AWS costs, fragile serverless systems, weak observability, broken RAG quality, or AI pilots that can’t safely reach production.
Prefer to write first? Email Rahul
$ tail -f prod/incidents.log
03:47:12PagerDuty ALARM token-spend-anomaly sev1
03:52:40root cause: unbounded retry loop, no cost ceiling
04:15:03mitigated. runaway spend stopped: ~$40K
04:15:09action: cost ceilings now default on every LLM call
Call me when
Most teams don't need more cloud jargon. They need to know what's expensive, what's fragile, what slows users down, and what can be safely changed this week.
Finance sees the number. Engineering sees hundreds of services. Nobody has a safe first move.
I start with cost allocation, idle inventory, traffic shape, and commitment risk before touching architecture.
The feature looks impressive in a meeting and then becomes expensive, slow, or untrusted with real users.
I inspect retrieval, context design, evals, fallbacks, and cost per request before blaming the model.
Every release needs extra human attention. That slows the team and creates fear.
First I check blast radius, deployment path, stateful dependencies, and rollback ownership.
Dashboards are present, but incidents still become log archaeology and Slack guessing.
I connect symptoms to traces, metrics, logs, ownership, and alarms that point to action.
Permission changes become production incidents waiting to happen, and nobody wants to clean them up.
I define account boundaries, environment contracts, permission guardrails, and IaC ownership.
Growth becomes a threat because failure modes, queues, database limits, and on-call paths are vague.
I model what fails first, then build guardrails around scale, retries, backpressure, and recovery.
12K+
LinkedIn followers
Public cloud and AI audience
5M+
monthly orders supported
High-scale commerce work
30-55%
cloud cost reduction
Up to 55% on selected sanitized work
AWS Pro
certified architect
Solutions Architect, DevOps Engineer
AWS
Community Builder
Recognized, serverless and AWS community
100+
mentoring sessions
Engineers, founders, and career-switchers
₹50L+/year in AWS waste removed for clients (~$60K+/year), from cost and reliability audits. Selected metrics are from projects where public or sanitized detail can be shared. Quotes reflect real engagements. Named references available under NDA for qualified inbound.
Visible pricing, fixed scope, findings your own team can execute. Deeper builds and ongoing ownership follow when the highest-risk path is clear.
From $2,000 · report in 10 business days
Teams about to ship, or already shipping with production pain.
A paid, fixed-scope review of an AWS or AI system that is live or close to launch: where cost, reliability, latency, and rollback risk hide, and what to fix first.
What's included
Includes a focused AWS Cost & Reliability Audit when the bill is the symptom.
From $1,500 · plan in 7 business days
Teams whose AWS bill keeps climbing and nobody owns FinOps.
I find what your AWS bill is quietly bleeding and hand you the remediation plan. You keep the savings forever.
What's included
Also available: GenAI / RAG readiness review, implementation sprints, and fractional platform architecture.
See all engagement typesNot thumbnail galleries. The useful parts are what failed, what changed, what improved, and what trade-off was accepted.
ASTM International · Enterprise engineering enablement
Ad-hoc AI coding → governed Claude Code delivery loop with standards, app KBs, skills, commands, Jira context, and PR review gates.
KFC Thailand · Imaginato
Peak-hour monolith failures + inflated EC2 → 5M+ orders/mo, P99 <200ms, ~30% infra reduction.
Enterprise Knowledge Base
30+ min document hunts → sub-10s answers; hybrid RAG + semantic cache cut LLM spend ~60%.
Rahul migrated our entire ordering pipeline to serverless and cut our AWS bill by 30% while handling 5M+ orders per month. He doesn't just architect: he ships production infrastructure.
Engineering Lead
Imaginato (KFC Thailand)
We needed someone who could design a multi-tenant SaaS architecture and actually build it. Rahul delivered 99.9% uptime with a 40% cost reduction. His Terraform modules are still the foundation of our infra.
Founder & CEO
ProdigyBuild
Rahul brought order to our chaos. He standardized our cloud architecture across teams with IaC templates that reduced manual setup by 70%. SOC2 compliance went from months to weeks.
Director of Engineering
ASTM International
Quotes reflect real engagements. Named references available under NDA for qualified inbound.
A real RAG lifecycle on AWS: authenticated request, semantic cache, vector retrieval, guardrails, then a Bedrock call — every step logged, evaluated, and capped by a hard cost-per-request ceiling. This is the difference between an AI demo and a system you can trust with real users and a real bill.
I'm Rahul Ladumor, a Principal Cloud & AI Platform Architect from Surat, India. I work close to teams that already have real users, real AWS bills, integration constraints, andreal production pressure.
9+ years in cloud and platform engineering. AWS Professional certified. 4x AWS Community Builder. Production AWS + GenAI delivery across enterprise, SaaS, consulting, and AI-driven development work. I care about systems that survive traffic, failures, and late-night incidents.
More about RahulVerifiable credentials
AWS serverless, event-driven architecture, FinOps, production GenAI, observability, and failure isolation.
A CDK TypeScript stack that routes S3 events through EventBridge properly: VPC placement, KMS, Secrets Manager, the cost model, and the failure modes most setups skip.
CodePipeline, CodeDeploy, and Auto Scaling in CDK: VPC, ALB, ASG, SSM config, and the lifecycle hook settings that keep deploys clean under real load.
The full web-app stack most tutorials skip: VPC isolation, Fargate on private subnets, Aurora with KMS, CloudFront, secret rotation, and the six operational gaps that page you at 2am.
I specialize in systems that need to survive production: serverless migrations, AWS cost optimization audits (typically 30-40%, up to 55% documented), event-driven architectures on ECS/EKS, GenAI/RAG infrastructure on AWS Bedrock, and multi-account cloud security. My value is highest when you need reliability, security, and cost control at scale.
Typical AWS + LLM engagements land around 30 to 40% when waste is structural: idle compute, wrong DB tier, unbounded model calls, missing lifecycle. On documented work, reductions reach up to 55%. I quote from utilization and billing data, not from a template. ₹50L+/year in AWS waste removed for clients (~$60K+/year), from cost and reliability audits.
I hold three AWS Professional certifications (Solutions Architect, DevOps Engineer, and Generative AI Developer), plus AWS Developer Associate and HashiCorp Terraform Associate. I'm also a 4x AWS Community Builder (Serverless).
Yes. I build production GenAI systems on AWS Bedrock including RAG pipelines, AI agents, and LLM applications. I handle the full stack: vector databases, prompt engineering, token cost monitoring, and audit logging. Currently studying Agentic AI at IIT Roorkee.
Yes: a free 30-minute call. You describe what’s going wrong, I suggest what to measure first, flag obvious cost and reliability risks, and say if I’m a fit. No commitment. Book from the contact page (Cal.com) or email hello@rahulladumor.com.
The first call is about finding the risky path, not selling a generic cloud package.
Prefer email? hello@rahulladumor.com
Book a paid Production Review