I build production AI systems - from LLM applications and autonomous agents to cloud platforms - helping companies turn AI experiments into reliable products.
About
I am a Senior AI Product Engineer focused on turning advanced technology into practical products. My work combines LLM applications, AI agents, full-stack development, and cloud architecture to create systems that are reliable, scalable, and valuable to users.
I enjoy solving complex engineering challenges and helping organizations move from ideas and experiments to production-ready AI solutions.
I build intelligent software products that connect advanced AI technology with real business impact.
Build intelligent applications using modern AI technologies.
Create complete software products from frontend experience to backend infrastructure.
Help teams design scalable AI systems.
Expertise
AI engineering, product development, and cloud infrastructure — combined to ship production systems that scale.
Featured Work
Not just what I can build — what I built, how it works, and the measurable results.
Conversational voice AI that automates patient communication workflows across 80+ healthcare EHR systems.
Impact
80+ EHR integrations · ~60% less manual workload
Secure RAG-based assistant that gives employees grounded answers from internal knowledge bases and business systems.
Impact
~70% faster knowledge lookup with cited answers
Multi-agent automation platform that turns operational workflows into reliable, observable AI-driven processes.
Impact
~50% fewer manual ops tasks via production agents
Experience
From Big Tech to AI startups — shipping production systems and intelligent products.
Designed and shipped scalable distributed systems supporting enterprise workloads using cloud-native architecture.
Adobe
Built enterprise software and AI-related systems that moved experimental capabilities into production product surfaces.
Prosper AI
Designed and deployed LLM-powered production systems serving real users — from architecture to launch.
Sapience AI
Built AI automation workflows using LLM-based and ML systems to reduce repetitive operational tasks for clients.
Process
A disciplined approach to turning AI ideas into reliable, production-grade software.
Start with the real-world challenge — who it affects, what success looks like, and where AI creates genuine leverage.
Define system boundaries, data flows, and integration points before writing code. Plan for growth from day one.
Ship AI features with rigorous engineering — LLM orchestration, agent workflows, and reliable backend services.
Launch with CI/CD, observability, and cloud-native infrastructure. Production readiness is non-negotiable.
Measure impact, iterate on user feedback, and continuously refine both the product and the AI systems behind it.
Technology
Not a skill list — systems and products shipped across AI, full-stack, and cloud.
Open Source / Engineering
Smaller demos and architecture sketches that show how I build RAG systems, agents, and voice pipelines — not just claim the skills.
Open engineering demo: ingest PDFs, retrieve with a vector store, and chat with citation-backed answers.
Lightweight agent runtime demonstrating tool calling, memory, and multi-step reasoning for automation tasks.
Architecture reference for speech → LLM → tool actions → TTS, with escalation hooks for human operators.
Engineering Notes
Short notes on shipping production AI — RAG, agents, scaling, and voice platforms.
How to design ingestion, chunking, retrieval, and evaluation so RAG answers stay grounded in production.
Planner loops, tool calling, memory, and the guardrails you need before agents touch real business systems.
Latency budgets, caching, cost controls, and observability patterns for shipping LLM features at scale.
Lessons from building conversational voice systems: turn-taking, integrations, and clinical-grade reliability.
Contact
Available for AI product engineering roles and consulting projects.
Let's discuss how intelligent software can help your business grow.
steincivil5@gmail.com