AI Systems · Databases · Cloud Architecture · Distributed Systems
20+ years designing and operating distributed systems, data platforms, and AI infrastructure at scale — now available for architecture advisory, technical reviews, and embedded principal engineering engagements.
Engagements range from one-time architecture audits to ongoing embedded advisory work.
LLM application architecture, RAG pipeline design, agent orchestration frameworks, evaluation infrastructure, and production guardrails for AI systems.
Schema design, query optimization, migration strategy, and operational runbooks for PostgreSQL, MongoDB, vector databases, and multi-model data platforms.
Multi-region architecture, reliability engineering, cost optimization, and system design for AWS, GCP, and Azure. CAP theorem tradeoffs made concrete.
In-depth technical review of existing systems: design gaps, scaling bottlenecks, security posture, and a prioritized remediation roadmap you can act on.
Fractional principal engineering, engineering strategy, hiring criteria, and technical due diligence for investors and acquirers evaluating a codebase or team.
Team workshops on distributed systems, database internals, and production architecture patterns. Interview-ready system design preparation for senior engineers.
No retainer traps. No mystery pricing. Three steps from first contact to active work.
30-minute free call. You describe the problem; I ask the questions that usually get skipped. No pitch deck, no NDA required to start.
Written proposal with clear deliverables, timeline, and fixed-price or retainer options. No surprise invoices at the end of the month.
Advisory calls, async Slack reviews, written architecture documents, or fully embedded work — matched to what your team actually needs.
The blog at rajivonai.com is the best signal of how I think about systems problems — architecture tradeoffs, failure modes, real-world database behavior, and AI infrastructure decisions written for practitioners.
Browse All Posts →20+ years designing and operating distributed systems, data platforms, and cloud infrastructure. I have worked across startups, scale-ups, and enterprise engineering teams on problems that span AI systems, database architecture, cloud reliability, and engineering organization design.
AKS Engineering (AKS Software Solutions LLC) makes that experience available on a fractional and project basis — for teams that need principal-level judgment without a full-time hire.
The engineering blog at rajivonai.com is a running record of what I have learned in production: what breaks, what scales, what the textbooks miss, and what actually matters when a system is under load.
Describe what you are building or the problem you are trying to solve. I respond within one business day.