Who gets hired and onto which teams
Of the 16 roles listed as of late August 2026, roughly half sit in functions that touch a buyer directly: Solutions Engineers for life sciences and the federal sector, Forward Deployed Engineers in Maryland and across the US, Enterprise Account Executives, and Customer Success Managers on the East Coast. The other half lives one layer back: Staff Performance Quality Engineers, a Senior Software Engineer on Patch Engineering and Vulnerability Remediation (based in Argentina), a Staff Software Engineer on Governance, IT Support Engineers spanning India, Mexico, and the European Union. The mix tells you where the company spends its hiring dollars, at the intersection of regulated AI buyers and the people who keep that buyer-facing software trustworthy.
The vertical focus explains the shape of that mix. Domino, backed by Sequoia, Coatue, Great Hill Partners, and Highland Capital, sells to "the world's most regulated enterprises" and the company describes its platform as powering over 20% of the Fortune 100. Customers named in Domino's own materials and in public talks include BNP Paribas, Allstate, GSK, and the US Navy. Hiring follows the buyer profile. A Solutions Engineer role for life sciences is scoped to "drug discovery, clinical analytics, regulatory workflows, omics processing, governance, reproducibility, and validation requirements." A Public Sector Solutions Engineer must navigate "federal security/compliance (FedRAMP, IL5)." A Forward Deployed Engineer in the public sector must "build and deploy production-grade AI and MLOps solutions within public sector customer environments." When a pharma giant or a Navy program officer is the buyer, the hire has to speak the buyer's language on day one.
That requirement produces a hiring funnel weighted toward senior individual contributors rather than junior generalists. Across the active 16 openings, only one or two are entry-level in flavor; most carry "Senior," "Staff," or "Lead" in the title. The Solutions Engineering function alone is hiring at every layer: a Senior Director of Solutions Engineering on the East Coast, solutions engineers for life sciences and the public sector, plus Forward Deployed Engineers embedded with the same buyers. The platform team — Governance, Patch Engineering, Vulnerability Remediation, Performance Quality — is staffing at the Staff level, which means they want engineers who already own systems, not engineers learning to.
The third leg of the mix is operations and support, and it stretches further across the map than the revenue side. IT Support Engineer postings list ten locations; Technical Support roles span Barcelona, Germany, and the US; a Quality and Compliance Analyst sits in India; a Vulnerability Engineer sits in India. A Technical Cloud Operations Lead, posted out of Argentina an hour before publication on the Built In board, is tasked with establishing "Domino's Cloud Operations function across customer cloud environments," a clear signal that the post-sale delivery footprint is still being built out, not maintained.
Three patterns hold across the postings. First, regulated-industry fluency recurs as a requirement: pharma, life sciences, federal, financial services, defense, each job description names the vertical's compliance regime. Second, customer-deployment experience weighs as heavily as product-building experience: Forward Deployed and Solutions Engineer roles sit alongside the Staff Engineering postings in roughly equal numbers. Third, the company staffs by region with intent — East Coast US for life sciences and public sector customers, India and the EU for support and security operations, Argentina for cloud platform work — so candidates who already hold the right to work in one of those geographies carry a structural edge that remote-first US applicants do not.
What it pays
Domino pays at the upper end of the enterprise AI platform market, and the spread between a Technical Writer at the bottom and a Software Engineering Manager at the top is roughly 3x. Levels.fyi puts the median yearly total compensation across roles at $228,850. The company's own live job board confirms the band: nine currently posted salaried roles run from $172,000 to $350,000, with a median of $250,000.
The cleanest window into actual offer ranges is the recent posting data. Six roles from the live board, all remote US:
| Role | Posted range (USD/year) |
|---|---|
| Senior Director, Solutions Engineering | $300,000–$350,000 |
| Enterprise Account Executive, Life Sciences | $250,000–$350,000 |
| Staff Product Manager, AI Factory | $225,000–$300,000 |
| Staff Software Engineer, Governance | $245,000–$275,000 |
| Solutions Engineer, Public Sector | $200,000–$250,000 |
| Enterprise Customer Success Manager | $177,000–$250,000 |
Two patterns jump out. The "Staff" prefix commands a real premium; the Staff Software Engineer, Governance role tops out at $275,000, while the Staff Product Manager, AI Factory role reaches $300,000, both above the median posted band. Verticalized sales and engineering roles — Life Sciences, Public Sector, Governance — carry the widest ranges, each spanning $50,000 or more between floor and ceiling. That spread lines up with the verticals Domino targets: regulated industries such as pharma, financial services, and national security, where "critical risk and critical innovation" drive premium pricing on both the customer and the talent side.
By discipline, Levels.fyi's role-level averages tell a consistent story. Engineering leads: Software Engineer averages $250,000, Data Scientist $247,230. Product and design trail closely: Product Manager $240,000, Product Designer $190,950. Business-side roles (Financial Analyst and Recruiter) both cluster at $228,850. Solutions Architect sits at $170,850, and Technical Writer anchors the floor at $165,825. These figures describe total compensation, so they include equity, which Domino structures on a standard 4-year vest with 25% in year one and the remainder monthly over the next three (Levels.fyi, 2026-09-03).
Salary.com's July 2025 dataset tells a different story worth flagging. Salary.com's figures put the average annual salary at $124,323, with a typical range of $109,691 to $140,173, far below the Levels.fyi and live-board numbers. The gap reflects what each source measures: Salary.com weights all job titles and pay elements heavily toward base salary, while Levels.fyi and the board capture total compensation weighted toward senior, technical, and revenue-bearing roles. Glassdoor's 210 reported salaries across 115 jobs land closer to the board figures. For candidates, those figures are the more useful reference point because they reflect what the company is actively posting and paying today.
Equity is the variable that most candidates underestimate. With a 4-year vest and 25% in the first year, a $300,000 offer carrying a meaningful equity slice can put total comp well above the posted band by year two. HireOven's analysis of the same nine postings finds most roles cluster between $212,500 and $262,500, with the full posted range stretching from $160,000 to $350,000, a 2.2x spread across the active requisitions. Levels.fyi found that candidates who negotiate, or work with a negotiation coach, average about $30,000 more per offer.
The takeaway for anyone sizing an offer: anchor on the live board, expect total comp to sit between $225,000 and $275,000 for most senior individual-contributor and manager-track roles, and plan for the high end of any posted band to require a Staff or Director prefix, or a vertical like Life Sciences or Public Sector where the customer mix justifies the premium.
How the hiring process works and what gets candidates through it
Most candidates who make it through Domino Data Lab spend close to three weeks in the pipeline. Glassdoor's aggregated interview data puts the average at 19 days across 38 submitted candidate reviews, with a wide spread between roles: Senior Technical Writer postings closed in roughly 7 days, while Product Manager searches ran about 42 days. That gap matters for applicants. If you are interviewing for a go-to-market or platform role, expect to wait a month-plus; if you are coming in for a documentation or enablement seat, you should hear back inside a week.
The funnel itself starts the same way regardless of the eventual title. According to a 2026 walkthrough of the application flow, candidates face a 20-to-30-minute recruiter phone screen as the first gate, where the recruiter sizes up your background, motivation, and basic fit before passing you to a hiring manager. Glassdoor's candidate write-ups echo that structure and add that what follows feels organized: candidates describe clear communication from recruiters and several opportunities to talk with people on the team they would actually join.
That does not mean the process is soft. Glassdoor's question bank for Domino Data Lab candidates runs to 41 items, with 38 reviews attached, a sample size large enough to give a real read on what gets asked. The bank splits across roles: 2 dedicated recruiter-screen entries, 3 Technical Support Engineer entries, and the bulk covering engineering and product tracks. For anyone targeting one of the nine roles currently posted on Zero G Talent's board, ranging from a Staff Software Engineer, Governance seat at $245,000–$275,000 to a Senior Director, Solutions Engineering role at $300,000–$350,000, expect a recruiter call first, then a hiring-manager conversation, then a technical or panel stage calibrated to the function.
The structural piece candidates underweight is the panel composition. Domino has been deliberate about sourcing diverse interview panels to limit unconscious bias, a practice that staff engineer Kathleen French described as standard on the engineering team, where she said the value she feels "is not despite being a woman, nor is it because I am one." For candidates, that translates into a practical signal: when you reach the technical round, the engineers in the room may not all look like the same person, and your read on team culture during that stage is real information, not theater.
Three things separate candidates who advance from those who stall. First, a coherent story on why enterprise AI platform work (specifically Domino's model-governance and MLOps surface area) fits your background. Recruiters screen for motivation, not just skills, and reviewers who progressed consistently described articulating that motivation crisply. Second, fluency in the actual technical surface of the role: the Glassdoor question bank skews toward scenario and system-design prompts for engineering candidates, and toward stakeholder-management prompts for customer-facing roles like the enterprise account executive life sciences seat posted at $250,000–$350,000 OTE. Third, a measured read on the team. The interview is bidirectional, and candidates who flagged concerns during the on-site stage reported those concerns were addressed rather than glossed.
The net effect is a process that rewards preparation over polish: a 19-day timeline, a structured recruiter-to-manager-to-panel flow, a published question bank large enough to study, and a panel composition designed to surface bias rather than hide it. Candidates who do the homework on Domino's specific enterprise-AI wedge and can speak to it plainly tend to move; those who treat it as a generic data-platform interview tend to bounce at the technical or hiring-manager stage.
Where the work happens
Domino keeps a small physical footprint for a company that sells an enterprise AI platform to global life-sciences, financial, and insurance customers. Built In's company profile lists three offices and roughly 200 total employees, with the headquarters at 135 Townsend Street in San Francisco. The company's own contact page, however, lists a mailing address at 548 Market Street in the same city, a PMB suite typical of a registered-agent setup, not a working floor, and a third-party directory places an address at 225 Bush Street. The discrepancy matters less than what it signals: Domino is a company whose center of gravity is digital, not its office lease.
The other two physical sites sit overseas. Built In records a UK office at 1 Poultry, London (EC2R 8EJ), and the company's job postings occasionally surface a Barcelona tag, with a Senior Technical Support Engineer role listed "Remote or Hybrid" out of Cataluña, Spain. None of the three locations is large enough to anchor a return-to-office mandate, and none needs to be. With about 200 people and customers spread across regulated industries where data often has to stay in-region, distributed work is closer to Domino's default than a perk.
That default shows up in the job board. Roles currently advertised there — a Senior Director of Solutions Engineering, an Enterprise Account Executive for Life Sciences, a Staff Product Manager for the AI Factory, a staff software engineer on governance, a Public Sector Solutions Engineer, and an Enterprise Customer Success Manager — all carry "Remote US" or "Remote US (East Coast)" as the location tag. The same is true of the public listings on Built In: a Technical Cloud Operations Lead in Argentina, a Staff Performance Quality Engineer somewhere in the US, and a Forward Deployed Engineer embedded with life-sciences customers, all marked "Remote or Hybrid." Built In also reports that the company maintains remote roles in the US, India, and Argentina as of mid-2026.
Domino's leadership has been explicit about the model. Built In's 2026 compensation and benefits profile quotes a Domino employee describing the policy this way: "the remote work policy at Domino is we hire where the talent is. So we actually have a pretty large remote workforce. We do our best to make sure that people still feel there's social interaction opportunities and we try to support people in a variety of different ways through benefits we offer." Built In's separate work-life-balance FAQ echoes the framing: policies "emphasize remote-first and hybrid options with flexible scheduling, enabling control over location and hours," with the caveat that the flexibility "helps integrate work with personal commitments when team norms align."
That last clause is the one to read closely. "Remote-first" at Domino does not mean every team runs the same way. The Built In company page classifies the workplace as "Hybrid" with "Typical time on-site: Flexible," language that puts the schedule in managers' hands rather than locking it in policy. Forward-deployed engineers embedded with life-sciences customers will travel to client sites by the nature of the work; the Cloud Operations lead and the platform-quality engineers stay close to production systems regardless of zip code. On-site time scales with the role, not with a corporate calendar.
For candidates, the practical takeaway is geographic: if you're a US-based applicant, expect a remote-first role that may ask for occasional travel to San Francisco or to a customer site; if you're based in London, Barcelona, Argentina, or India, your position is most likely a regional one tied to either a customer-facing pod or a specific market. Domino's 200-person headcount is too small to support a real campus, and its enterprise customer base is too distributed to demand one. The office is a place to convene, not a place to work from.
Who thrives here
A candidate's CV opens the door at Domino; whether they keep the seat depends on a different set of traits. The hiring bar described earlier — domain credibility, customer-facing fluency, and the ability to ship production-grade code or product — converges on a profile the company repeatedly signals it wants: people who can operate close to the customer without losing the engineering rigor required to deliver against an enterprise procurement clock.
The clearest signal sits in the role mix itself. Of the 9 salaried roles currently posted to that board, 6 carry "Solutions," "Customer Success," "Account Executive," or "Public Sector" in the title, meaning the company's growth hinges less on pure research talent and more on practitioners who can translate platform capability into customer outcomes. The posted bands tell the same story: a Senior Director of Solutions Engineering tops the range at $300,000–$350,000 USD/year, ahead of several engineering tracks. The implication is direct: the people who ascend here pair technical depth with the patience and discipline to run a multi-stakeholder enterprise deal or deployment.
Specific postings sharpen that picture. The Enterprise Account Executive, Life Sciences role sits at $250,000–$350,000 USD/year and asks for familiarity with regulated industries; the Solutions Engineer, Public Sector band of $200,000–$250,000 USD/year signals that domain knowledge (pharma, government, financial services) converts into leverage. Candidates who can credibly talk to a biostatistician, a procurement officer, or a FedRAMP reviewer appear to have a structural advantage over generalists, regardless of coding chops.
The patterns that surface across employee commentary point to a few consistent traits. Comfort with ambiguity shows up repeatedly in Glassdoor and Blind reviews: the company's roadmap touches model governance, AI factories, and platform integrations simultaneously, and reviewers describe product direction shifting as customer feedback lands. Employees who frame that as opportunity rather than chaos tend to last. So do those who default to written communication — engineering, product, and field roles post detailed specs, RFCs, and customer-facing documentation, and the asynchronous culture assumes fluency there.
A subtler signal: the compensation spread. Across the live postings, the salary range runs from $172,000 to $350,000 USD/year, with a median around $250,000 USD/year, and the variance is driven mostly by role and scope rather than location, given the remote-first structure. Candidates who negotiate from a position of demonstrable impact (a previous deployment at scale, a reference customer, a quantified outcome) capture the upper end of those bands. Those who lean on competing offers alone, without a track record to point at, tend to land lower.
Finally, the traits that don't help: passivity in customer settings, resistance to documentation, and a preference for greenfield builds over hardening an existing platform. Domino is a mature product company with regulated buyers; the work is incremental, integration-heavy, and frequently unglamorous in the quarters between major releases. People who describe themselves as "early-stage builders" sometimes find the rhythm wrong.
The closing exercise for serious candidates: study the job description for the specific role you want, pull two or three recent Domino blog posts or customer announcements from domino.ai, then map a specific past project of yours onto a problem the company describes as live. Candidates who can do that in concrete terms tend to hear back; the rest tend to learn what the company already knew about its own gaps.
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