I help platform and DevOps teams ship production AI systems on AWS — with clear architecture, cost-aware design, and systems your team can actually run and own.
These are infrastructure decisions that benefit from someone who's already solved them at scale. That's what I do.
Best fit: AWS-first engineering teams with existing infrastructure and engineering maturity that want to move fast on AI without creating chaos or runaway costs. Not early-stage prototypes or one-off experiments.
Before we build, we map. A deep-dive technical review of your AWS environment to identify where AI fits, what architecture makes sense, and where cost and operational risk show up. Most teams are overspending on inference, retrieval, or compute — they just don't know where yet. The audit makes that visible.
This is where the roadmap turns into production systems your team can extend immediately. I embed with your team for short, high-intensity sprints to build the AI infrastructure designed in the audit. Training happens through the build — your team learns by shipping.
For teams that need ongoing guidance or more complex rollouts. Fractional architecture leadership, platform strategy, or long-term modernization — scoped to your constraints.
If your team needs upskilling without a full implementation engagement, I offer hands-on training tailored to your stack. Not slides and theory — real architecture patterns, real services, real deployments.
Every engagement starts with a conversation. Most clients follow the Audit → Sprint path, but we'll figure out what makes sense for you.
30 minutes. We discuss your stack, your goals, and figure out whether an Audit, Sprint, or Advisory engagement is the right starting point. No pitch.
A paid deep-dive into your AWS environment. You get a written architecture roadmap, a cost audit, and a prioritized execution plan. This is where most engagements begin.
Short, focused implementation cycles — weeks, not months. I embed with your team and we ship the highest-value parts of the roadmap together.
Documentation, handoff, and a team that understands every decision behind the system. You can maintain and extend it without me.
I'm Saurav, the engineer behind CloudYeti. I spent 6 years at Amazon — first as a Senior Technical Account Manager managing $100M+ enterprise cloud accounts, then as a Software Development Engineer building LLM platforms, RAG pipelines, and agentic AI workflows.
I hold 12 AWS certifications including Solutions Architect Professional, AI Practitioner, and DevOps Professional. My YouTube channel has over 1.3M views from cloud and DevOps engineers learning to build production AI systems.
I started CloudYeti because I kept seeing the same pattern: platform teams with deep infrastructure expertise that were ready to add AI capabilities but needed someone who'd already built these systems at scale to accelerate the path. That's what I do.
Book a free 30-minute discovery call. No pitch — just a clear conversation about what's working, what's not, and what to do next.
Book a Free Discovery Call →