Daniel Noel

Builder, tinkerer, and operator who has been writing code since age 10. Two decades of launching startups, scaling platforms to millions of users, and shipping production AI: voice sales agents, live AI coaching, RAG pipelines, production knowledge bases, and custom domain models. I am also an AWS cloud architect, Kubernetes expert, and site reliability engineering operator. My last contract was a $2M build for live AI sales coaching and AI voice agents at Luminary Life. I am available now for an AI-first VP Engineering, Head of Engineering, hands-on CTO, or senior AI engineering leadership role.

• Voice sales agents: production AI agents that handle inbound and outbound sales calls with real-time STT, LLM reasoning, and TTS.
• Live AI agent coaching: systems that monitor live sales calls and surface real-time coaching cards to reps without interrupting the conversation.
• RAG & knowledge bases: retrieval-augmented generation systems backed by vector databases (Redis Vector DB, pgvector) for multiple client knowledge bases.
• LLM integrations: GPT-4o function-calling agents embedded in Slack for unified company AI interfaces; custom fine-tuning and prompt pipelines for domain-specific tasks.
• Custom LLM training: fine-tuned and built custom LLMs trained entirely on proprietary client data, keeping sensitive information fully in-house with zero exposure to third-party model providers.
• Custom model training: built and trained custom ML models to score complex non-linear relationships into clean reductive scores, enabling business logic to act on nuanced signal without manual analysis.
• Privacy-preserving AI: designed and deployed AI systems with data privacy as a first-class constraint, including on-premise inference and architectures that never expose user data to external APIs.
• ML model lifecycle: trained image classification networks, ran high-capacity inference workloads, and converted models for TensorFlow and CoreML deployment.

• Languages: C#, Python, Go, C, C++, JavaScript (React, Vue, Angular), Swift, PHP, Assembly, Bash, PowerShell, Rust, Ruby on Rails.
• AI / ML: LLM APIs (OpenAI, Anthropic), RAG pipelines, vector DBs, voice agents, PyTorch, TF, CoreML, image classification.
• Cloud: AWS (VPC, EC2, ECS, RDS, S3, Lambda, CloudFront, IAM, Route 53, SQS, SNS, CloudWatch), GCP, Azure, Vercel.
• AWS cloud architecture: production architecture, networking, IAM, cost control, capacity planning, managed services, migration paths, and operational ownership for business-critical systems.
• Kubernetes & containers: Kubernetes expert across deploys, security, monitoring, custom autoscaling, Helm, Docker, vSphere, VirtualBox, and Docker Swarm.
• Site reliability engineering: SLO-minded operations, on-call systems, incident response, release safety, observability, capacity planning, autoscaling, backup/recovery, and infrastructure cost management.
• Databases: MySQL, PostgreSQL, MongoDB, Redis (Cache + Vector), Cassandra, Snowflake.
• Observability: ELK Stack (APM, Kibana, Filebeat), Prometheus, Grafana, custom metric injectors, on-call alerting.
• Networking & security: OSI 1–7, TLS/SSL, VPN, OAUTH, gRPC, WebSockets, Vault, Falco, Cert-Manager, PGP, Sn1per.
• CI/CD & DevOps: GitHub Actions, TeamCity, Jenkins, Helm, Octodeploy, private Docker registries, ECS.
• Media & rendering: FFMPEG, ImageSharp, server-side PDF rendering, 3D (Unity, Unreal).
• ETL & data: Pipelinewise, Snowflake, full analytics data design.