Rahul LadumorPrincipal Cloud & AI Platform ArchitectAWS ProCommunity Builder
I help SaaS and enterprise teams fix AWS platforms that keep failing, get AI features through production and security review, and take control of systems after a difficult handover, so your engineers can spend their week on the product again.
Reach me directly:rahuldladumor@gmail.comContact form
$ 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
Who this is for
For founders and engineering leaders whose AWS-based product has real users, and whose team needs senior help with recurring failures, rising costs or a blocked AI launch.
The first step is the same every time. You share architecture evidence and read-only access, bounded in writing. In10 business days you get a risk register with the evidence behind each finding, a target architecture, and the order to fix things in, walked through with your engineers. If you want hands-on help after that, we scope it from the findings.
Based in Surat, India (IST). Works with US, EU, and APAC teams. Reply typically within one business day.
Six problems that show up after launch, from a bill nobody can explain to a platform nobody trusts at 10x traffic. Each card says how it hurts and where I start looking.
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.
Services and AI tools can reach more than they should, while auditability and human approval remain unclear.
I define account boundaries, least-privilege tool access, approval controls, audit evidence, 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.
9+
years in production
AWS, platform, and GenAI delivery
5M+
monthly orders supported
High-scale commerce work
30-55%
cloud cost reduction
Up to 55% on selected sanitized work
99.99%
platform uptime
QSR e-commerce ordering platform (Thailand)
₹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.
The audit tells you what is fragile, what it costs, and what to fix first. Your own team can execute the plan, or you can bring me in for AI productionization, a project rescue, or ongoing architecture ownership.
From $2,000 · one bounded system · report in 10 business days
AWS-based SaaS and enterprise teams approaching launch or carrying material production risk.
A paid, fixed-scope audit of one production system or mature AI workflow: reliability, IAM, data boundaries, observability, cost, deployment, and rollback.
What's included
Includes a focused AWS Cost & Reliability Audit when the bill is the symptom.
After evidence
Paid engagement · fixed scope
Move a mature AI prototype into controlled production with narrower tool permissions, stronger retrieval evidence, evals, fallbacks, human approval, and workflow-level cost controls.
Discuss productionizationAfter evidence
Paid engagement · scoped phase
Stabilize an expensive, fragile, undocumented, or partially abandoned AWS platform without beginning with a risky rebuild.
See how project rescue worksAfter evidence
Monthly retainer · scoped hours
Principal-level AWS and GenAI ownership without waiting for a full-time hire or bringing in a large consultancy.
Discuss fractional ownershipEach one says what was failing, what I changed, what improved, and which trade-off we accepted to get there.
Enterprise Knowledge Base
30+ min document hunts → sub-10s answers; hybrid RAG + semantic cache cut LLM spend ~60%.
Major QSR e-commerce platform (Thailand) · Imaginato
Peak-hour monolith failures + inflated EC2 → 5M+ orders/mo, P99 <200ms, ~30% infra reduction.
Enterprise client (NDA)
Manual VPC sprawl + quarterly audit pain → standardized IaC, 70% faster setup, findings down 47 → 3.
30%AWS bill cut · 5M+ orders/mo
“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.”
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
Quotes reflect real engagements. Named references available under NDA for qualified inbound.
Architecture evidence and read-only access where it helps, bounded in writing before anything starts. In 10 business days you get a written risk register, a defensible target architecture, and a prioritized remediation roadmap, plus a 90-minute walkthrough and two weeks of async follow-up questions.
Report first: it keeps my incentives honest. Implementation support and fractional-architect retainers are available afterward, and most clients use their own team with my report as the roadmap.
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.
Start with one bounded system, the evidence you already have, and the production decision that cannot wait. Worldwide remote: US, EU, and APAC hours covered from IST.
Prefer email? rahuldladumor@gmail.com
Request a paid reliability audit