Daniel Raymond
I build production AI systems — and help organizations adopt them.
A hands-on AI transformation and platform leader with 15+ years across software engineering, DevSecOps, cloud infrastructure, machine learning, and agentic AI. My work spans both sides: designing production systems and building the onboarding, policies, and workflows that help teams actually use them.
AI Adoption & Enablement
Onboarding, responsible-use policies, workflow design, internal advocacy, and practical support for teams integrating AI into daily work.
Agentic Systems & AI Platforms
Agent orchestration, persistent context, tool use, evaluation, approval boundaries, observability, and production reliability.
Document Intelligence & Automation
OCR, retrieval, structured extraction, classification, validation, and automated document workflows.
Secure Platform Delivery
Python, Nix, containers, Kubernetes, AWS, CI/CD, DevSecOps, reproducible environments, and operational controls.
The shortest path to a proof of concept is rarely the right path to a reliable system.
Production architecture, organizational adoption, agent platforms, and open source. Each one solved a real problem at scale.
- 01 Company-Wide AI Adoption & Enablement Led ATA's transition to an AI-native operating model — onboarding, responsible-use policies, agent-assisted workflows across engineering, QA, product, and leadership. $250K+ estimated annual efficiency gains Python · LLM · Nix · Policy · Enablement 2025–26
- 02 Della + ExoBrain Autonomous-Agent Platform Custom agent platform with persistent identity, durable memory, proactive initiative, sandboxed code execution, multimodal interaction, and real-time private interfaces. Production-grade autonomous-agent research platform Python · FastAPI · SQLite · NixOS · Local LLMs · WebSockets 2026
- 03 Document Intelligence Platform OCR pipelines, structured extraction, and retrieval workflows eliminating manual processing for selected document classes. 90%+ extraction accuracy. 90%+ extraction accuracy · Eliminated manual processing for selected workflows Python · Tesseract · AWS Textract · Label Studio · Extra Trees 2026
- 04 AI-Assisted QA Automation Agent-assisted test generation and regression hunting. Owned architecture and implementation from scratch — no QA headcount growth required. 80% automated test coverage · 50% reduction in regression defects Python · LLM · CI/CD 2026
- 05 Lockheed Martin Enterprise Automation Led a seven-person team on a $500M defense program. Automation platform eliminating two weeks of manual effort per release cycle. Influenced 150+ engineers. $1.2M estimated annual savings · 90% deployment time reduction Terraform · Kubernetes · Python · DevSecOps 2022–24
- 06 WebbDuck Self-hosted SDXL image studio: text-to-image, img2img, inpaint, smart extend, upscaling, LoRA management, searchable local gallery, plugin ecosystem. Production-ready local creative stack · open source Python · FastAPI · Diffusers 2026
Architect for what comes after the demo.
Retrieval, orchestration, evaluation, infrastructure, security, approvals — the work that lets teams actually depend on the system.
Autonomy with kill switches.
Governance, auditability, and human approval where they matter — useful agents in real organizations, not lab toys.
Measurable behavior over vibes.
Regression checks, eval harnesses, observable workflows. If you can't measure it, you don't really ship it.
Adoption is half the work.
The best platform is the one people understand, trust, and actually use. Onboarding and enablement aren't afterthoughts.
Tools I've put into real production — across hosted and self-hosted.
Frontier assistants where they earn their cost. Local runtimes where privacy or latency demands it. Glue that ages well.
Building an AI team or platform?
I'm open to conversations about AI engineering leadership, applied AI, platform architecture, enterprise enablement, and hands-on agentic systems.