Chief Technology Officer

Chief Technology Officer

Location: Kirkland, WA (HQ) — on-site · Type: Full-time · Reports to: Founder & CEO

Compensation: $300,000–$400,000 base salary · annual executive bonus · founding equity grant, 4-year vest

About Hussh

Hussh (hussh 🤫) is an AI-first research, machine-learning, and product organization building Private Agent One — a private personal AI agent. The human owns their information, holds the keys to it, and shares it only by their consent, through our PCHP (Personal Consent Handshake Protocol). It is the architecture — every system we build runs underneath it.

The product line is live and widening: Private Agent One is available now, free for every American; iMoney — investing and money movement in which the agent proposes and the human approves, every time — reaches production launch on December 27, 2026; Puppy One, a private computer for the home, is taking reservations; One for business and the information marketplace are in build. Beside the product company sits a sister business: a permanent-capital asset manager (Fund A / Alphabet 27), run on the same doctrine. We are a 19-person company, 100% founder-funded, with no outside investors. Today, the founder is the technology thesis, the architecture review, and the tie-breaking vote on every hard technical question.

About the role

We are seeking our first Chief Technology Officer — the single authority over what this platform becomes: which systems are worth building, on what architecture, with which models, at what cost — and the leader who makes those decisions true in shipped product.

The span is the whole technical company, under one hand: agent systems and product engineering; models, post-training, and evaluation; inference on device and in the cloud; the consent and vault architecture; data; and security. A personal vault is the highest-value target in consumer computing — its compromise is not an incident, it is the end of the company, and its design has to assume a motivated adversary and a careless moment. The agent must be model-agnostic: the best frontier models and the best on-device models behind a single harness, routed by evaluation rather than allegiance, so no provider can ever hold a user's agent hostage — including us. And relevance here is inverted: ranking and recommendation run over a person's own information, for that person's benefit.

In your first 90 days: the technology thesis is written — the bets, the anti-bets, the build/buy/partner calls, each with the evidence that would change your mind; the harness and evaluation architecture is decided, with evals as the gate nothing ships past; the vault and consent architecture has had its first full adversarial review under your authority, with findings owned and dated; and iMoney's path to December 27 is under technical control, with the correctness bar for money movement defined by you. Six months in: iMoney has shipped on its date; One is running its model portfolio behind one evaluation gate, with cost per user served falling on a curve you can show; the engineering organization is structured as the thesis made flesh; and the founder is out of technical tie-breaking, because you are in it. The standing standard for every hire here is outcomes worth 100–1000× their pay. The CTO who sets the platform every other seat builds on clears that bar by construction — or the seat was staffed wrong.

Responsibilities

- Own the technology thesis: the multi-year bets on models, architecture, devices, and infrastructure — reviewed against evidence, and revised in writing when the evidence moves

- Own the agent harness and model strategy: selection, integration, and routing across the frontier model providers (OpenAI, Anthropic, Google, xAI, Meta) and open-weight models — every model behind one evaluation gate, every routing decision measured, no provider privileged by relationship over results

- Own evaluation as the shipping authority: the benchmarks, regression suites, and human-evaluation design that decide what ships — a product claim our evals cannot back does not ship, and you are the person who says so

- Own the consent and vault architecture: PCHP as running code, not a document — key management and recovery with no back door, the guarantee that no machine touches a person's information without a consent event that person can inspect and revoke

- Own security as architecture: threat models for a platform holding a person's whole information life, the review discipline for every system that touches it, and the incident posture — designed in advance, rehearsed, and honest

- Own inference economics: serving architecture, latency and cost budgets, quantization and distillation for on-device models, and the hybrid routing between the person's devices and our cloud — intelligence that gets cheaper per user as we scale

- Own the money systems' technical bar: iMoney's ledgers, sweeps, and approval flows — double-entry correctness, idempotency, reconciliation, and the rule that no agent action moves money without the human's explicit approval, enforced in the architecture rather than in a policy

- Own the platform beneath the portfolio: the shared services, data infrastructure, and relevance systems that every product is built on — one platform, so each product makes the others stronger

- Own the technical organization: hire the leaders and the bar — founding engineers, research engineers, design engineers — set the review culture and the operating cadence, and represent Hussh's technology as a peer to the frontier labs and the partners whose platforms we build on

- Own the technical research agenda: the IIT Kharagpur lab and the Stony Brook AI3 partnership pointed at the problems the platform actually has — personal models, consent systems, on-device intelligence — with results that come home into product

You may be a good fit if you

- Have 15+ years of experience in engineering and technical leadership, with the last 5 years building products in AI — and depth in at least one of: personal information systems, subscriptions, advertising, or relevance and ranking — shipped to real users

- Have been the final technical authority on a platform that real revenue and real users depended on, and can walk through the two or three decisions — what you chose, what it cost, and what you would do differently

- Have run product engineering and infrastructure under one hand, or can show why the split failed: you think in systems that include the serving bill

- Have built production systems on frontier models and under on-device constraints — you know what quantization does to quality, and what a harness owes its models because you have written one

- Have designed security-critical systems where the asset was other people's trust — keys, payments, health, identity — and your threat models were written before the incidents, not after

- Have hired senior engineers and managers whose own careers accelerated under you, and set a bar your organization kept after you left the room

- Write the thesis yourself: your technical documents survive skeptical reading by people who disagree with you, because the reasoning is checkable and the anti-bets are named

- Care about taste: which problems are worth solving, which results are real, which demos are lying — and say so in the room, early, when it is cheap

Strong candidates may also have

- Time at a frontier AI lab or a category-defining product company in a senior technical leadership seat

- Both consumer and enterprise platforms in your record

- Hardware or edge-computing depth: silicon-aware software, devices that ship to homes

- Money-movement systems — brokerage, payments, or banking rails — where correctness was regulated, audited, and personal

- A research-community presence: papers, open-source systems, or standards work

Compensation

The annual base salary range for this role is $300,000–$400,000 USD. The role also carries an annual executive bonus tied to company and technology outcomes and a founding equity grant (4-year vest). Where you land in the range depends on the record you bring, and we will tell you where you land and why.

Benefits

Comprehensive health, dental, and vision coverage. A 401(k) plan. Employer-matched contributions to Trump Accounts. Support for continuing education, retooling, and retraining — including AI courses, which we actively encourage. Above all: you will work with the latest AI technologies every day, and the expectation — for engineers and non-engineers alike — is to become expert in using them, running evals on your own work until it reaches an A+ standard.

Benefits are subject to the terms of the applicable plans and to eligibility requirements, in accordance with federal and state law.

1. Tell us about the technology bet you made that the room disagreed with — the bet, the evidence you had at the time, and how it ended.

2. Our evaluations decide what ships. Describe an evaluation system you built or ran that stopped something from shipping — what the gate measured, what it caught, and what changed because it existed.

3. Give a real example where you materially cut cost per user served (or cost per inference) without losing quality — the starting number, the ending number, and the levers you pulled.