Architecture & System Design
- Domain-driven design and service boundaries
- Event-driven systems and workflow orchestration
- Modular monoliths and microservice architectures
- Multi-tenant SaaS and platform design
AI Applications · RAG & Hybrid Search · Full-Stack Delivery
About & Expertise
I’m Olatunde Adedeji, an AI applications architect and full-stack engineering leader focused on designing and delivering production-grade AI systems, data platforms, and cloud-native products from architecture through deployment.
Who I work with
I work with founders, product teams, and engineering leaders who need to move from promising ideas to systems that can actually run in production. That may mean an agentic workflow, a grounded RAG assistant, a hybrid search layer, or a full AI-enabled SaaS platform.
My focus is on clear architecture, maintainable implementation, and delivery choices that fit the realities of your stack, team, and operating constraints. Across fintech, learning platforms, internal tools, and AI-native products, I build systems that are meant to be owned, extended, and trusted over time.
How I typically help
- Designing AI features and workflows that fit existing systems and real business constraints.
- Architecting retrieval layers, vector-backed search, and data pipelines for grounded AI products.
- Building full-stack prototypes that evolve cleanly into maintainable production systems.
- Helping teams improve delivery across evaluation, deployment, observability, and long-term AI operations.
Technical Expertise
Practical depth across AI applications, full-stack product engineering, data systems, and cloud-native delivery.
Agentic & Retrieval Systems
- RAG systems, grounded generation, and hybrid search
- Vector databases including pgvector, Pinecone, and Chroma
- Prompting, guardrails, evaluation, and reliability
- Agentic workflows, assistants, and tool-using AI systems
AI Product Engineering
- React and Vue application development
- FastAPI, Django, and Flask backend systems
- REST, GraphQL, and real-time API patterns
- Background jobs, queues, and workflow automation
Data & Decision Systems
- PostgreSQL, pgvector, and data modeling
- Redis, caching, and performance-oriented backend design
- ETL pipelines and retrieval-oriented data preparation
- Ranking, scoring, analytics, and experimentation workflows
Cloud, Delivery & Operations
- AWS-first and cloud-native application architectures
- Docker, Kubernetes, and scalable deployment patterns
- CI/CD with GitHub Actions and modern release workflows
- Observability, logging, reliability, and AI operations
Leadership & Collaboration
- Technical leadership, mentoring, and architectural guidance
- Architecture reviews, RFCs, and design communication
- Cross-functional collaboration with product and engineering teams
- Technical writing, education, and knowledge transfer
Certifications & Continuous Learning
Ongoing investment in cloud architecture, data systems, AI engineering, and technical craft.
Cloud & Infrastructure
- AWS architecture and cloud platform learning
- OCI AI and data-focused certifications
Data & AI Engineering
- Data science, machine learning, and AI engineering programs
- Ongoing study in data-centric AI, MLOps, and retrieval systems
Professional Practice
- Technical writing, teaching, and practitioner communication
- Continuous learning across full-stack and AI system delivery
Ready to discuss your next AI product or platform?
If you’re exploring an agentic workflow, an AI-enabled product, a grounded RAG assistant, or a new SaaS platform, let’s talk about what you’re building and what it will take to deliver it well.