I'm a technical consultant and the founder of PNXStudios. As a founder myself, I also work with fellow founders and teams shipping systems that have to hold up in production — when an AI-accelerated prototype shows its seams, a codebase buckles under scale, or a problem nobody's cracked needs an experienced pair of eyes. Distributed systems, connected products, real-time video, applied AI. When the problem is harder than it looked, I can debug the system underneath, find the architectural mistake, and tell you what will break in production.
AI is one thread in a broader engineering career — but it is a long one, and it's the thread people ask about most. So here's the specific history. AI consulting is having a gold-rush moment, and for a lot of people it's genuinely new. My own applied-AI work started just over two decades earlier: the AI Group at Countrywide Bank in the early 2000s, building expert systems for automated property valuation and loan appraisal. Followed in 2005 by a Guinness World Record for ChessBrain — a distributed chess engine running across 2,070 machines in 50+ countries. Chess is one of the fields AI used to measure itself against; I was building on that side of it. In the years since, the work has tracked the field as it widened. By 2013 I was doing natural language processing the hard way — PostAnalyzer, a Python and NLTK engine that pulled key phrases out of forum and social streams, scored their richness, and normalized slang, profanity, and misspellings into something a machine could reason over. That is the lineage a transformer architecture later turned into the LLMs everyone now reaches for — I was working the problem back when it still meant NLTK pipelines and hand-built feature rules. The thread kept widening from there, across modalities: real-time pose analysis in computer vision, speech-to-text transcription at scale, RAG pipelines, and LLM infrastructure. As CTO at Skafos AI, I led the team building an e-commerce product-discovery platform on vector image similarity — embeddings over product imagery, the same idea that now powers vector search and RAG.
What that means today: when the AI-accelerated prototype starts hitting its limits, I can debug the distributed system underneath, untangle the architectural shortcut, and tell you which parts of the stack will hold up and which will break under realistic load. If you shipped fast with Cursor, Claude Code, Lovable, or v0 and you're starting to wonder whether the foundation will survive real users — I can share what I think holds up, what needs to be rebuilt, and in what order.
For businesses trying to figure out where AI actually fits — not the pitch-deck version, but the one you have to ship, support, and measure — I separate signal from theater, identify workflows where AI moves the needle, and sequence pilots before you commit the roadmap. Same twenty-five years of applied AI, pointed at a different problem.
Current work in this thread: PNXStudios — AI-powered movement analysis from multi-angle video, for training, sports performance, and rehab; and Solrac — a self-hosted coding agent over Telegram that defaults to free local LLMs and escalates to Claude only on demand, with hard cost caps and an append-only audit log.
I'm also an active member of Utah's Silicon Slopes tech community, where I write regularly on AI, startups, and the craft of building. The pieces I'm proudest of are collected on my blog.
Fractional CTO, technical diligence, board-adjacent advisory, engineering-org design. I've directly reported to CEOs and CTOs at five companies and helped prepare five profitable exits.
For founders and growth-stage teams that need senior judgment without a full-time hire.
Hands-on system design and implementation. Distributed systems, event-driven backends, AI/ML infrastructure, real-time video, IoT. I write production code — 10K+ GitHub commits and counting. Usually brought in when the problem is harder than it looked — legacy system rescues, performance bottlenecks nobody's traced, architectural decisions with real downstream cost.
For teams that need a senior engineer who can both design and build the system.
If you shipped a prototype quickly — built fast under pressure, demo-grade, or AI-accelerated — and you're worried the foundation won't hold at scale, I can do a thorough review: what works, what doesn't, where the landmines are, and what to fix first. Thirty years of production engineering behind the assessment, including hands-on computer vision, speech-to-text, RAG, distributed systems, and video at scale.
For founders and teams who shipped a prototype fast and want a senior read before scaling.
For established businesses assessing where AI actually fits. I help separate signal from theater, identify the specific workflows where AI would move the needle, assess integration with the systems and teams you already run, and sequence pilots before committing the budget or the roadmap. Twenty-five years of applied-AI perspective pointed at your operational reality.
For operators and teams exploring how AI fits into the business — before the roadmap, headcount, or spend.
Two smaller-scope engagements that come up often. A senior read on an in-flight project — a vendor build, an internal roadmap, a team you're not sure is tracking right — where I assess scope, architecture, people, and delivery signals and tell you where the risk actually sits. Or technical vetting before a commitment: senior engineering hires, fractional-CTO searches, or agency selection, with resume review, technical screens, and final-round sit-ins.
For founders and operators who want a second senior opinion before committing to a build, a hire, or a vendor relationship.
If your situation doesn't map cleanly to one of these, tell me anyway — we'll sort it out on the first call.
Flywheel Sports ran 42 brick-and-mortar cycling studios nationwide plus FlyAnywhere — a live and on-demand video platform streaming to connected bikes at home, in direct competition with Peloton. I directed 20 engineers building technology across the combined business: production studio automation, the video migration infrastructure (Verizon EdgeCast to Akamai during a live outage), and the systems tying the physical and digital sides together. FlyAnywhere ran on Hydra, the microservices framework I created that Flywheel later open-sourced.
FlyAnywhere was selected as one of Oprah's top picks for the 2019 Holiday Season. I subsequently supported the $25M sale of Flywheel Sports' technology to F45 Training.
Brought on as F45's SVP of Technology & Head of Engineering to help prepare for F45's successful 2021 IPO on the NYSE — I was on the floor for the opening bell. Reporting to the CTO, I led engineering teams across six locations in four countries — New York, California, Texas, Sydney, the Philippines, and Vietnam — with about a dozen direct reports from Directors through Senior Architects.
Built F45's first AWS EKS Kubernetes cluster and led a platform-wide security upgrade — a new API Gateway and authentication service that now protects every one of the 1,500 studios. Created a container-first local development environment spanning multiple languages, platforms, and stacks.
Carlos provided me invaluable support in his role as SVP of Technology & Head of Engineering. He is highly regarded by our engineering team members and was a capable SVP of Technology and Head of Engineering. If afforded the opportunity I would absolutely hire and work with him again.
Over a two-year engagement, I shipped eighty-four merged PRs to Moose, an open-source analytical backend framework on ClickHouse and Redis. Built the coordination layer that lets multiple instances cooperate safely without stepping on each other — connection pooling, distributed locks, and leadership election for multi-instance deployments.
Spearheaded the initial effort to deploy Moose on Kubernetes in Google Cloud, taking it from single-box to a production-grade cluster deployment. Ran the security and reliability passes that hardened the framework for real-world use.
Also brought F45 Training in as Fiveonefour's first client — a relationship carried over from my time as F45's SVP of Technology — then joined the delivery team with key code-level contributions to the Lionheart 2.0 launch. The project rebuilt F45's analytics platform on Moose to serve 50K+ daily users and process over a billion biometric data points per week.
The rebuild boosted dev velocity for user-facing analytics by 10×, cut cloud infrastructure costs by more than half, and unlocked a year-long feature backlog. Downstream at F45: +70% member satisfaction, +44% app virality, and 2.5× higher lifetime value among members engaging with the new analytics.
Founded a B2B SaaS platform for movement-based practitioners — martial arts schools, yoga and Pilates studios, dance academies, and physical-therapy practices. Designed and shipped the platform end-to-end: mobile capture app, multi-camera 3D motion-capture pipeline, GPU-accelerated server-side media pipeline, multi-camera video player, 3D pose viewer, SaaS web app, and programmatic video editor. Built SOMA on top: AI-based coaching analysis of 3D movement.
PNXPlayer is a 29K-line TypeScript video player distributed via CDN and npm — a manager-based architecture spanning 28+ subsystems, with synchronized seek across stacked video elements, AirPlay and Chromecast, A/B loop, and transcript search with word-level timing. PNXCamera, the mobile counterpart for iOS and Android, synchronizes 4K capture across N devices via network channels with NTP-style time sync and audio-beep cross-correlation — sub-millisecond frame alignment, with network traffic in lobby state cut 77% via change-detection broadcasting. Photogrammetry-grade capture meant patching react-native-vision-camera at the native layer — Swift/AVFoundation on iOS, Kotlin/Camera2Interop on Android — for deterministic focus, exposure, and white-balance lock.
To manage the engineering work behind all of this, I built (a soon to be Open Sourced) agentic development workflow on the Claude Agent SDK with permission policy, per-chat cost caps, and multi-engine routing across Claude tiers and a local Ollama — anchored by a 450-document hybrid RAG (pgvector HNSW + Postgres tsvector, 70/30 semantic plus full-text with issue-ID exact-match boosting), exposed to LLM clients via custom MCP and UTCP servers.
As a co-founder of Flywheel Sports, we prided ourselves in attracting and hiring an unusually passionate and hard working staff who cared for the business as if it were their own. Carlos is one of those people.
Carlos is a unique individual who combines a rare capability to look at a problem as a whole, at high level, and can also break it down to the smallest excruciating detail. He finds common language with senior executives who don't understand technology, while having complete respect of his developer team. At Flywheel he served as VP of Engineering, but also acted in the capacity of the CTO.
Carlos and I worked together at Skafos AI while he was our CTO. Under his leadership, our team onboarded several new engineers, undertook a significant architectural shift, and grew our customer base from 0 to several launch partners in a few months.
When an external enterprise vendor nearly wiped out all of Flywheel's online videos, Carlos developed a replacement service and migrated the missing files to an alternative cloud solution within five days. Absolutely incredible.
First distributed network in history to play against an internationally ranked human opponent in a public exhibition — ChessBrain, 2,070 machines across 50+ countries.
F45's 2021 NYSE IPO. $25M Flywheel sale to F45. Acquisitions: Estate Assist (DocuSign), IGT (GTECH, $6B), inSparq (Adiant).
Earlier consulting engagements include Activision, Disney Interactive, IBM, and Symantec.
FlyAnywhere — Flywheel Sports' connected-fitness platform — was selected as one of Oprah's top picks for the 2019 Holiday Season.
Applied AI since the early 2000s: the AI Group at Countrywide Bank, distributed AI on ChessBrain, early NLP with NLTK, vector image similarity at Skafos AI, today's RAG and LLM infrastructure.
Co-authored Advanced Macromedia Flash MX ActionScript in Action (Prentice Hall, 2002) and the ChessBrain chapter in Advanced Intelligent Paradigms in Computer Games (Springer, 2007). Peer-reviewed work at IEEE CIG and ICGA Journal; writing in Linux Journal, IBM developerWorks, and O'Reilly. CIO Review (2019), “Evolution of Wearables and Connected Fitness.”
RedisConf 2018, 2019, 2020 — the 2020 talk on BioGraph, a human-physiology model on RedisGraph, was selected as a best talk. EmpireNode 2016. BoF Linux Conference Copenhagen 2005, keynote.
GitHub commits since 2010. Maintainer of Hydra and other open-source projects.
Twelve-plus commercial products across the career — from business applications and computer games to distributed AI, connected fitness, and movement analysis.
Member, Association for Computing Machinery and Institute of Electrical and Electronics Engineers. Member and contributor, Silicon Slopes Technical Community, where I write on AI and startups. Redis Stars honoree.
Custom PCB design and manufacturing, ESP32 / Arduino / Raspberry Pi firmware, BLE, 9-DOF IMU/AHRS, biometric sensors, PlatformIO. The physical-product side of connected products.
Director of Software Development at iPayment, Inc. — grew engineering from 3 to 17 as company revenue moved from $50M (2010) to $70M (2011). iPayment was later acquired by Paysafe Group in 2018.
I take on a small number of concurrent engagements. Common shapes: fractional-CTO retainers (a few days a month), fixed-scope builds (three to six months, deliverable-based), and short advisory or diligence work (hours to weeks). We can discuss your needs during our first call.
Based in Salt Lake City, UT. I work remotely by default and travel for kick-offs, on-sites, and the occasional offsite. I've led and collaborated with engineering teams across seven countries — the US, Australia, the Philippines, Vietnam, India, Pakistan, and Ukraine.
Work where the technical problem is genuinely interesting, the team can execute, and the outcome matters. I'll pass when the fit isn't right — it protects both sides.
Bias toward solid engineering: design docs before big builds, runbooks for things that have to be operated, post-mortems for things that broke. Measure before optimizing. The output of senior help should reduce ongoing burden on the team, not add to it.
Working systems the team can operate without me — observability that points at real problems, runbooks for the on-call hours that haven't happened yet, decisions documented well enough that someone can revisit them in a year. Senior engagements should make the next year easier, not harder.
Thirty minutes by video or phone. No deck. Tell me what you're trying to build or untangle and where you're stuck. I'll tell you whether I can help, whether someone else is a better fit, and what next steps might look like. Book a 30-minute call.
The best way to start is a short email with two or three sentences about what you're working on, where you're stuck, and what success would look like. If you're in the Salt Lake City area, I'd love to meet up in person.
cjus@ieee.org