I design AI systems and build them end-to-end — from scalable serverless architectures to production-ready mobile apps.
I'm an experienced AI Integration Architect focused on building scalable systems and automating workflows using the latest AI technologies. I don't just advise — I design the system and build it, end-to-end.
My work spans the full stack: from designing agentic frameworks and LLM pipelines to shipping production mobile apps. Notable projects include architecting a mobile sports wager tracking app with OCR capabilities and building data reliability layers for e-commerce systems.
From rapid MVP to production-grade — I work across the AI stack with a focus on real-world impact.
Design and deployment of LLM-powered agents, multi-agent frameworks, and autonomous workflow systems. Integrating AI into existing products without disrupting them.
Cloud-native, serverless backends built to scale. AWS Lambda, API Gateway, and DynamoDB as a foundation for reliable, cost-efficient systems.
Production-ready mobile apps with React Native/Expo. OCR integration, real-time data, and polished UI — from prototype to App Store.
Extracting structured data from documents, images, and forms with high accuracy. Building pipelines that turn unstructured content into actionable data.
Ready system architecture for SaaS, AI, and cloud applications. Scalable, secure, cost-effective — with a 10-day delivery guarantee.
Getting to working product fast, with production-grade foundations. Internal tools, workflow automation, and B2B products that clients actually ship.
Recent projects spanning agentic AI, mobile apps, and data infrastructure.
A React Native/Expo iOS app for tracking sports bets backed by an AWS serverless architecture. Features OCR bet slip scanning with confidence warnings, real-time NBA game data, and timezone-aware ET date indexing for accurate game scoping.
A multi-agent orchestration framework for complex, multi-step AI workflows. AERO provides structured coordination between specialized agents with built-in reliability and observability.
Designed and built a data reliability and validation layer for high-throughput e-commerce systems — ensuring consistency, catching pipeline failures early, and enabling confident downstream automation.
A B2B platform turning prospect data into qualified pipeline via AI-personalized LinkedIn messaging. Integrates enrichment APIs and LLM-driven drafting to scale outbound without sacrificing quality.
Beyond tools, I bring an operational engineering mindset — reliability, observability, and maintainability built in from day one.
Understanding your goals, constraints, and existing systems before touching a line of code.
Designing the system — components, data flows, integrations — with clear documentation.
Execution with iterative delivery. Transparent progress, realistic timelines, no surprises.
Production-ready delivery with documentation your team can actually maintain and extend.
"Shaleen has been great to work with. He's very thoughtful in how he approaches system design and took the time to clearly break down the architecture, tradeoffs, and roadmap for the project. He communicates well, explains complex technical concepts in a way that's easy to understand, and has been collaborative in aligning the build with my vision. I also appreciate his transparency around scope, timelines, and what's realistically needed to build a usable product. Overall, very professional and knowledgeable — I'd definitely recommend working with him."
Based in Acton, MA — working with clients globally. I focus on AI integration, system architecture, mobile development, and rapid MVP builds. Reach out and let's scope your project.
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