Thomas Davis

Principal-level engineering across AI, product development, and full-stack architecture. Most recently led production AI capabilities for an HR-tech SaaS, from agentic features to the underlying services.

• Built production AI copilots with tool calling over customer data, response evaluation, and streaming interfaces.
• Developed autonomous agent workflows for generating reports, presentations, and PDFs from live business data.
• Shipped high-scale analytics and real-time collaboration systems, including server-side compute, caching, and concurrent-edit integrity testing.

Built the frontend of an Electron-based Bitcoin wallet for issuing, managing, and trading digital tokens.

• Developed React and Redux interfaces for secure wallet operations.
• Implemented local key-management and transaction-signing workflows, keeping private keys on the user's device.

Full-stack engineering and technical leadership for an Australian cryptocurrency exchange.

• Built trading interfaces and exchange services using React, Apollo, Node.js, and Rails.
• Integrated liquidity providers and optimized SQL queries across tens of millions of market records.
• Worked across infrastructure, product design, and deployment on Docker, Heroku, and GCP.

Developed a cross-platform React/Redux application for web, iOS, and Android using a shared application architecture.

• Built a PWA with React Native wrappers for mobile platforms.
• Worked with PostgreSQL, Redis, DynamoDB, AWS, Heroku, Fastly, and Cloudflare.

Developed digital campaigning infrastructure and civic participation tools.

• Built a Ruby on Rails action centre for contacting elected representatives.
• Developed campaign tools and integrations that lowered barriers to public participation.

Joined as a frontend engineer and became CTO, leading product engineering, infrastructure, and a small development team.

• Built a Backbone.js single-page application backed by Rails and MongoDB.
• Managed developers and designers and migrated infrastructure from Heroku to AWS.

Developed civic technology and online campaigns opposing mass surveillance.

• Helped build The Day We Fight Back and related campaigns.
• Campaigns generated 37 million banner views, 100,000 phone calls to Congress, 500,000 emails, and 250,000 signatures.

Created a widely read educational resource for JavaScript and Backbone.js.

• Reached over two million unique visitors annually.
• Generated 25,000+ ebook downloads and 300,000+ YouTube views.

Developed frontend applications and widgets for enterprise editing software, including API design, documentation, and UI/UX work.

A dependently typed programming language and compiler for AI learning systems. Compiles model mathematics, training loops, host code, and GPU instructions into self-contained executables without conventional machine-learning runtimes.

• Trained a 1.38B-parameter language model over 5.84B tokens on two H100 GPUs, averaging 247,865 tokens/sec with an Alpha-generated executable.
• Built native NVIDIA GPU code generation, FP8 kernels, attention, multi-GPU NVLink communication, and direct driver interfaces without CUDA, PyTorch, or NCCL on the training path.
• Developing dependent types, formal verification, and compiler infrastructure for agent-driven discovery of new algorithms and learning systems.

Founded the open standard for representing resumes as JSON. Now an ecosystem of schemas, themes, developer tools, AI job matching, and agent integrations.

• 7,000+ GitHub stars across the ecosystem and tens of thousands of users.
• 52 first-party themes, a public registry, in-browser editor, CLI, and MCP integrations.
• AI job matching with embeddings, hybrid retrieval, and LLM reranking; improved precision at five from 0.2 to 0.8 in evaluation.
• Maintains the schema, CLI, core libraries, jobs package, and Rust serialization tooling.

Co-founded one of the web's largest open-source JavaScript and CSS content delivery networks, now operated with Cloudflare.

• Used by millions of websites and serves billions of requests monthly.
• 10,000+ GitHub stars.
• Helped establish a community-maintained infrastructure project that became a widely used part of the web.

An evidence-first knowledge system for AI agents, built in Rust and PostgreSQL. Stores contradictory claims with provenance, bitemporal history, query-time reconciliation, and formal verification.

• 42M+ statements and millions of evidence links, with large-scale LLM extraction and agentic-memory tooling.
• Custom query language, predicate alignment, temporal reasoning, and provenance-aware access control.
• 62 Lean 4 theorems proving core invariants, plus signed and reproducible knowledge releases.

An experimental computing platform where language models generate literal executable machine bytes rather than source code, which are validated and executed on a custom virtual computer.

• Designed the ANMA-1 virtual instruction set, validator, interpreter, and WebAssembly execution path.
• Built an interactive browser-based virtual computer with memory, registers, devices, and visual execution tracing.
• Developed checker-assisted agent loops, independent correctness tests, and formal verification experiments.

Developing a general-purpose agent execution harness for persistent sessions across web, CLI, and local development environments.

• Designing durable agent orchestration, resumable sessions, and execution across local devices and remote workers.
• Exploring multi-computer execution, session branching, and long-running autonomous development workflows.

An experimental mathematical reasoning platform connecting ideas, Lean 4 formal proofs, theorem libraries, and AI agents.

• Exploring machine-checked mathematical reasoning and proof-assisted AI research.
• Developing agent-friendly interfaces for theorem exploration, proof construction, and verification.

Tool Package Manager for AI Agents. Discovers, validates, and exposes npm packages as tools through MCP, SDKs, and command-line interfaces.

• Automatic npm tool discovery and sandboxed Deno execution.
• MCP aggregation and agent tooling infrastructure.
• Platform for building, sharing, and extending AI agents.

A semantic validation system for AI-generated code, using domain specifications to detect inconsistencies and implementation drift.

• Declarative domain specifications using entities, signals, measures, and rules.
• Schema, structure, and LLM-based domain validation with actionable feedback for coding agents.

An adversarial research-paper replication engine that extracts scientific claims, constructs evidence graphs, runs independent checks, and records reproducibility verdicts.

• Processed the Kolmogorov-Arnold Networks paper: 102 claims extracted, 24 reproduced, and 3 contradicted.
• Combines LLM extraction, simulations, mathematical checks, and provenance through Donto.

An AI-powered Discord agent with 80+ tools, multi-database memory, code execution, and autonomous improvement workflows.

• Code execution across 42+ programming languages.
• Agent tooling for software development, communication, and GitHub-driven self-improvement.

CLI for using language models to optimize functions, validate functional equivalence, and benchmark implementations across languages and providers.

• Supports JavaScript, TypeScript, Python, Rust, and Go.
• Includes automated verification, performance comparison, a terminal UI, and cost analysis.

Open-source language revitalization platform for Aboriginal Australian languages, combining dictionaries, community recordings, translation, and speech technology.

• Built neural TTS and ASR pipelines for low-resource languages using VITS, wav2vec2, phonemic dictionaries, and fine-tuning.
• Developed language datasets, translation experiments, evaluation tools, and an Android keyboard.
• Designed consent-first, community-governed workflows where real speaker recordings take precedence over synthetic speech.