Varick Agents — Staff / Senior Engineer

davidjoseph-co; San Francisco (CA); On-site; USD 225,000 - 300,000; Full time

Job summary

Varick Agents, a San Francisco startup, is seeking a Staff/Senior Engineer to lead platform architecture for AI deployment in enterprise environments. You will own the build‑vs‑buy decisions and define system direction.

You will drive production systems, guide a growing team, and align research with production realities, delivering scalable, reliable AI workflows for Fortune 5000 clients.

The role offers on-site work in the SF Financial District and a direct path toward CTO‑level impact.

Qualifications

• Experience shipping production AI/ML systems.
• Ability to own architecture and engineering standards.
• Strong leadership and team-building capabilities.
• 5 days in-person at SF Financial District.

Responsibilities

• Lead Varick's platform technical direction and set engineering standards.
• Architect compound AI systems and governance for production deployment.
• Drive weekly production releases and scale team from 5 to 50 engineers.
• Mentor engineers and establish scalable processes.

Skills

Production AI/ML systems

System architecture

Leadership

In‑person work in SF

Tools

Kubernetes

Distributed systems

Cloud architecture

Job description

Varick Agents — Staff / Senior Engineer

Type: Full-time | On-site (5 days) | San Francisco, CA (Financial District)Compensation: $225,000–$300,000 + 0%–3% equityHiring count: 1Visa sponsorship: None availableReports to: Founders (direct) — no named hiring manager in the role page

About Varick Agents

Varick Agents is a San Francisco–based AI startup valued at $30M following a $3.8M seed round. They help enterprises move AI from prototype to reliable production by embedding with customers, auditing their operations, and building the agents, integrations, and workflows needed to transform how those businesses run. A flagship surface is the AI FDE — an agent built to do the work of a forward‑deployed engineer: scoping complex problems, writing and integrating code, and standing up production systems alongside customer teams. Founding thesis: the hardest part of enterprise AI is not the model, it's deployment, reliability, and trust.

Founded: 2026 | Team size: 11–50 (Seed) | Funding: $3.8M seed | Valuation: $30MIndustry: AI ToolsWebsite: varickagents.comOffice: San Francisco, CA (Financial District)

Why Candidates Should Join

• Founding scope, CTO track: Own the entire technical vision and architecture; explicit, direct path to CTO.
• Build a platform, not features: Every client deployment compounds the product; 100% production deployment rate with immediate, measurable impact.
• Enterprise access at the seed stage: Direct line to Fortune 5000 decision-makers, working on systems that improve with every customer.

Intake Call Summary

• Not available. The role page includes an intake video player only; the captured HTML contains no transcript, so there is nothing to summarize. Transcribe/re‑capture if you want this populated.

The Role

Lead Varick's platform technical direction — design the architecture, set engineering standards, and own the build‑vs‑buy calls that decide whether Varick becomes a generational platform or stays a services business. This is the person defining the system, not a senior IC inside someone else's org.

What You'll Be Doing

• Own the technical architecture: agent orchestration, process‑mining infrastructure, diagnostic pipelines, and the control plane that turns audit outputs into deployed AI systems
• Architect compound AI systems running inside Fortune 5000 environments: multi‑step agents, retrieval pipelines, evaluation frameworks, human‑in‑the‑loop governance
• Set the engineering pace — Varick ships to production weekly, not quarterly; drive velocity, cut scope ruthlessly
• Recruit, mentor, and lead engineers; set code‑review standards, establish process, and build a team that scales from 5 to 50
• Bridge research and production: stay current on foundation models, agent frameworks, inference optimization, tool use, and long‑context reasoning, and translate what's useful into production

Tech stack: Not specified by the client. Technologies referenced in the role: agent orchestration, retrieval pipelines, evaluation frameworks; infra depth (Kubernetes, distributed systems, cloud) listed as nice‑to‑have.

Requirements

• Production AI/ML systems: inference, orchestration, evaluation, monitoring
• High agency, ownership mentality
• SF Financial District, 5 days in‑person

Green Flags

• Real, deep understanding of how scale actually works in production.
• Can architect on a whiteboard without leaning on slides.
• Has shipped production systems they personally designed.
• Strong opinions, easily updated when shown they're wrong.
• Visible curiosity about agent and AI infrastructure specifically.
• Capable of being CTO of Varick in a few months

Red Flags

• Title says "staff" but they've only ever consumed abstracted infra.
• Can't code live in the interview.
• Hand‑wav y on scalability ("we'd just use Kubernetes").
• Ego that won't compress to a 10‑person team.
• Coast mode from a comfortable big‑tech role.
• No top AI lab or founding‑engineer‑at‑AI‑startup pedigree — weighted especially heavily until the client defines what counts as a "top AI lab."
• Outside the target experience band (6+ years engineering, 2+ years staff, principal, or founding) — penalized on distance from the range, not disqualifying. Years of experience is not a hard filter; recent company quality and demonstrated output are.

Role Details

Salary$225,000–$300,000Equity0%–3% (max 3%)ExperienceTarget band 6+ yrs eng, 2+ yrs staff/principal/founding — scored as a Red Flag (penalty scales with distance), not a hard requirement. Years of experience is not a hard filter; recent company quality and demonstrated output are.On‑site policy5 days/week in-person, SF Financial DistrictVisa sponsorshipNone availableEmployment typeFull‑timeLocationSan Francisco, CA

Body Nice‑to‑Haves (not in the sidebar cards)

• Agent systems, compound AI workflows, or LLM‑powered applications in production
• Background in process mining, workflow automation, or enterprise integration
• Infrastructure depth: Kubernetes, distributed systems, cloud architecture
• Previous founding engineer or CTO experience at a venture‑backed startup
• Published research or significant open‑source contributions in AI/ML

Interview Process

Pipeline stages as listed (no descriptions provided beyond the stage names):Stage 1 — Pending ApprovalStage 2 — First RoundStage 3 — Second RoundStage 4 — Third RoundStage 5 — On SiteStage 6 — OfferStage 7 — Hired — Candidate accepts and starts.