Agentic AI · RAG & Hybrid Search · LLM Applications · Cloud-Native Platforms

AI Applications Architect & Full-Stack Engineering Leader

I design and deliver production-grade AI applications, grounded retrieval systems, and cloud-native platforms from product architecture and backend workflows to deployment, monitoring, and scale.

Collaborating with teams and clients globally

What are you here for?

Core Expertise

I build production-grade AI applications across four connected layers: grounded retrieval and agentic workflows, full-stack product engineering, decision and data systems, and reliable cloud-native operations.

Agentic & Retrieval Systems

Designing AI systems that retrieve, reason, and act within real workflows with grounding, evaluation, and reliability built in from the start.

  • Agentic workflows, assistants, and tool-using AI systems
  • Enterprise RAG, semantic retrieval, and hybrid search
  • Grounded generation, citation-aware responses, and abstention logic
  • Evaluation, guardrails, safety, and reliability for LLM systems

AI Product Engineering

Building full-stack AI applications that connect user experience, backend services, and model-driven workflows into maintainable products.

  • AI-native applications in React and Vue
  • Backend systems with FastAPI, Django, and Flask
  • API design for models, tools, workflows, and integrations
  • Multi-tenant SaaS platforms with embedded AI capabilities

Decision Intelligence & Data Systems

Turning structured and unstructured data into explainable decision workflows, retrieval pipelines, and scalable analytics foundations.

  • Data pipelines, ETL workflows, and analytics foundations
  • Embeddings, vector stores, and knowledge retrieval architectures
  • Ranking, recommendation, and scoring systems
  • Experimentation, monitoring, and product analytics for AI systems

Platform Reliability & AI Operations

Operating AI systems with the deployment, observability, and governance practices needed for production use and long-term maintainability.

  • Cloud-native architectures across AWS and modern container platforms
  • Containers, Kubernetes, and scalable inference services
  • CI/CD for software systems, ML workflows, and LLM applications
  • Observability, reliability engineering, and responsible AI operations

Case Studies

Selected examples of how I design AI systems in practice, from enterprise prioritization and grounded document intelligence to responsible monitoring and operational governance.

RiskRank Copilot

A full-stack prioritization platform for evaluating and ranking enterprise AI use cases across business units.

Transparent weighted scoring, actionable recommendations, and portfolio-level governance visibility.

React 19FastAPIWeighted Scoring Engine

View case study

EviVault Assistant

A full-stack document intelligence platform for answering internal policy and operational questions with grounded evidence.

Citation-backed retrieval, confidence-aware responses, and abstention logic for trusted enterprise Q&A.

React 19ChromaDBRAG Pipeline

View case study

FairWatch

A healthcare AI monitoring platform for tracking model health, fairness disparities, and alert workflows in real time.

Disaggregated metrics, severity-based alerts, and auditable incident management for responsible AI operations.

React 19FastAPIRecharts

View case study
Agentic Workflows · Intelligent Systems · RAG Architecture

Ready to Build Your NextAI Product or Platform?

Let’s design and deliver an AI system your team can actually use, operate, and trust, from retrieval workflows and product architecture to deployment, monitoring, and long-term maintainability.

Author
Technical books, courses, and long-form practitioner writing
AI
SaaS platforms, RAG systems, decision intelligence, and monitoring workflows
Global
Collaborating with teams and clients across domains and geographies