AI Agent Engineering
Build AI applications with bounded tools, explicit execution policies, meaningful evaluations, and observability that makes behavior inspectable.
EvidenceAgent Reliability Lab · Enterprise RAG Assistant
Explore service AI systems · backend architecture · integration
Engineering Reliable AI & Backend Systems.
I help startups and engineering teams design, build, and improve AI agents, enterprise Java services, and mission-critical API integrations.
20+ years engineering Enterprise architecture Hands-on development
Engineering principles 01 — 04
01
Bounded systemsExplicit limits, policies, and failure modes
02
Observable behaviorTraceable decisions and inspectable evidence
03
Resilient integrationIdempotency, timeouts, and recovery paths
04
Practical architectureTrade-offs matched to real constraints
Architecture that holds up under pressure
Where I help
Complex systems. Clear engineering.
Focused consulting for teams building AI applications, integrating critical services, or evolving a platform under real-world constraints.
Backend & API Integration
Design Java services and external integrations that account for retries, duplicate requests, partial failure, and ambiguous outcomes.
EvidenceSpring Boot Integration Lab
Explore service Architecture Consulting
Get a clear view of system constraints, architectural trade-offs, delivery risks, and the practical next steps to improve a platform.
EvidenceEnterprise platform and distributed-systems experience
Explore service Selected independent work
Engineering, made inspectable.
Three independent portfolio demonstrations exploring reliability in agent systems, external integrations, and enterprise retrieval.
AI Agent Engineering01
Agent Reliability Lab
A Java agent lab that puts application-owned controls around model-proposed actions.
Backend & API Integration02
Spring Boot Integration Lab
A fulfillment gateway designed to behave conservatively when a partner API is unreliable.
Enterprise AI & Retrieval03
Enterprise RAG Assistant
A knowledge assistant prototype that applies document permissions before retrieval and keeps sources inspectable.
How I work
Thoughtful design.
Useful delivery.
Good engineering starts with context and ends with a system the team can understand, operate, and evolve.
- 01Understand the constraints
Clarify the business need, existing systems, risks, and team realities before choosing a solution.
- 02Make trade-offs explicit
Design a practical architecture that explains what it optimizes for and what it does not.
- 03Validate critical behavior
Exercise failure paths, contracts, and operational assumptions, not just the happy path.
- 04Leave the team stronger
Deliver maintainable implementation, clear documentation, and decisions the team can build on.
Perspective earned over time
Broad context.
Hands-on judgment.
More than two decades in software engineering across e-commerce, financial technology, and investment banking, including engineering leadership and distributed platform delivery.
Large-scale digital commerceFinancial technology platformsBanking and real-time systemsEngineering leadership
More about Kai Next step
Have a complex engineering challenge?
Let's discuss a focused architecture review, integration project, or AI engineering engagement.