Job intelligence
Staff Network Engineer (AI Infrastructure)
vCluster Labs
Executive opportunity brief
The decision in one screen
A compact evidence-first read of compensation, flexibility, mobility and what still needs verification. No universal quality score is used.
Fast read
Opportunity DNA
There is a useful advantage here: location flexibility looks unusually broad. Still, the salary benchmark is still shallow could change the fit.
The range is usable, but the comparable sample is still too shallow for a strong relative-pay call.
No material geography, office-attendance or timezone restriction is visible in the available wording.
The listing does not make the minimum education or experience threshold clear enough yet.
Sponsorship and relocation support are not clear from the current listing.
Part of the application route can be assessed, but the full external process may contain additional steps.
At least one recent enabled source can still renew this vacancy.
This fingerprint summarizes what is clear, constrained or still unanswered in the current listing. It is a reading aid, not an overall job score.
Decision evidence check
5 of 5 core facts stated
This checks whether the listing states the facts that commonly change an employment decision. It measures disclosure completeness, not whether the opportunity is good or bad.
Facts already stated
- Compensation
- Work arrangement
- Advertised location
- Application closing time
- Employment type
Core evidence complete
All five core facts are stated. Other details can still matter, so continue with the qualification, mobility, employer and application checks below.
Advertised location is not proof of work authorization, sponsorship, or legal eligibility. Unknown information is not a negative score; verify those questions separately.
Decision levers
What could make or break the fit?
Reasons to look closer
- Location flexibility looks unusually broad: The available wording supports high Remote Freedom without a material geography, office-attendance or timezone restriction showing up.
Trade-offs to weigh
- The salary benchmark is still shallow: Pay is disclosed, but the current comparison pool is too small for a strong relative-pay conclusion.
Questions worth asking before you invest more time
- Confirm whether a degree is actually required, preferred, or replaceable with equivalent experience.
- Confirm the actual minimum experience requirement rather than assuming preferred background is mandatory.
- Ask whether visa sponsorship is available before investing significant time in the application.
These questions come from details the listing leaves open. An unanswered point is not treated as a disadvantage.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing states usable structured compensation, but the current role sample is still too small for a reliable disclosure-rate comparison.
Compensation counts only when amount, ISO currency and supported pay period are all known.
At least ten current comparable roles are required before HPJ publishes a disclosure percentage.
Employer-level comparison is withheld until enough current employer listings are available.
This compares salary-disclosure behavior in current visible listings. It does not compare raw salary amounts across currencies, infer undisclosed pay as zero, or rate employer quality.
Private offer & negotiation lab
Turn an offer into evidence, not guesswork
Enter an annual base offer and, if you want, your own target. HPJ compares only within one explicit currency and never chooses a target for you.
Negotiation evidence available: advertised pay range, strong decision evidence.
Enter an annual base offer to compare it with explicit same-currency evidence. HPJ will not suggest a target for you.
Review the full package · 10 terms
Mark what is confirmed, what needs clarification and what you want to prioritize. These choices and notes stay in this browser.
Usable advertised compensation is available.
Variable compensation is mentioned; verify amount, formula, target and eligibility.
Equity or long-term incentive language is mentioned; verify grant type, vesting and valuation basis.
Retirement or pension benefits are mentioned; verify employer contribution and vesting.
Health-benefit language is mentioned; verify coverage, dependants and employee cost.
Paid-leave language is mentioned; verify the exact entitlement and carry-over rules.
A work-arrangement signal is available; verify schedule details before relying on it.
Relocation support not established
Sponsorship not established
A review cycle is mentioned; verify timing and whether compensation can change at that review.
Questions worth taking into the offer conversation
- What retirement or pension contribution does the employer provide?
- How much paid leave is provided and what are the carry-over or blackout rules?
- If relocation is relevant, what expenses, timing and repayment conditions are covered?
- What exact sponsorship or work-authorization conditions apply to this role?
- When is the first performance and compensation review after joining?
Skill bridge
What does this role connect to?
The listing contains useful skill signals, while the current occupation sample is still too thin for a broader comparison.
Skills named in this listing
Shared with the current career sample
The occupation sample is still too thin for a reliable shared-skill comparison.
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Kubernetes, Linux, and Python rather than relying on a keyword-only claim.
Skill signals come from explicit text mentions. A mention is not automatically a requirement, and absence from the current top-skill list does not make a skill rare or unimportant.
Application Decision Lab
Turn the listing into a preparation plan
Separate what the listing actually states from what you still need to prepare or verify. Your selections and short notes stay in this browser and are never submitted to High Paid Job.
Kubernetes
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Linux
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Python
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Salesforce
This skill or technology is explicitly mentioned in the available listing text. A mention is not automatically a mandatory requirement; prepare a concrete example only if it is relevant to your experience.
Questions worth resolving before you rely on the opportunity
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
- Application process: What interview, assessment, portfolio, reference or screening stages are part of the hiring process?
Decision analysis
What the listing really tells you
Staff Network Engineer (AI Infrastructure) at vCluster Labs becomes easier to judge once pay is visible, but the benchmark is still thin, the location rules are clear enough to judge, and the application route gives a few useful clues are viewed together. Here is the current read from the information available.
Pay is visible, but the benchmark is still thin
A usable USD salary is available, but there are not enough comparable current observations for a strong percentile statement yet.
The location rules are clear enough to judge
The work-location pattern is “Highly location-flexible”, with Remote Freedom at 96/100.
The application route gives a few useful clues
Provider-mediated application path. The external application may contain additional steps that are not visible from the listing itself.
Source continuity adds useful context
1 recent enabled source can currently renew this vacancy across 1 source classes. That improves traceability, although it does not verify the employer itself.
How this analysis is assembled
This read combines the structured details currently available for pay, flexibility, qualifications, mobility, application effort and source continuity. Missing facts are left open for you to verify.
Analysis evidence coverage
How much analysis can the current evidence support?
This title does not yet fit a reliable comparison family, so a pay percentile is not shown.
Measures observable location flexibility and explicit restrictions; it does not determine whether remote work is personally desirable.
The configured source supplied structured salary fields, a usable currency and a focused comparison value.
The listing was posted about 8 days ago.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
There is no universal opportunity score because pay, flexibility and access matter differently to different people. Compare Jobs lets you weight the evidence around your own priorities.
Decision checklist
What is supported, uncertain or worth checking?
This checklist separates supported strengths, visible cautions and missing evidence. It is not an overall recommendation or guarantee that the job is suitable for you.
Supported strengths
- The available work-location evidence indicates strong location flexibility.
Visible cautions
No specific caution is supported by the currently available evidence. This does not prove that none exists.
Still unknown
- There is not enough comparable salary evidence to establish this job’s current pay position.
- Visa sponsorship is not established by the available listing data.
Pay vs. barriers
Opportunity Efficiency not assessed
The current pay position is not reliable enough to weigh compensation against the stated barriers.
- Current comparable pay position is unavailable.
- Education requirement is not established.
- Required prior-experience level is not established.
This section weighs pay context against clearly stated barriers without collapsing unlike requirements into one universal score. Degree, experience, licensing, clearance and location limits remain separate, and missing qualification details stay unknown.
Beyond the headline
Not enough evidence for a hidden-value finding
Potential hidden value appears only when several distinct non-pay advantages are actually supported. Missing requirements or benefits are never counted as positives.
The observable Remote Freedom evidence is strong and contains few explicit restriction signals.
Still check: The current application path is provider-mediated rather than directly classified as an employer-authorized or official route.
Hidden Value is an experimental evidence summary, not an investment-style score or guarantee of employability. It only uses explicit current listing evidence and does not infer that an unmentioned qualification is unnecessary.
Explainable opportunity highlight
Why this opportunity stands out
These are supported signals from the current listing and comparison sample—not a guarantee that this is the best job for you.
The source provides structured salary information with a comparatively focused range, improving the usefulness of pay comparisons.
The observable work-location signals indicate unusually strong location flexibility.
Compensation intelligence
How competitive is this pay?
This title does not yet fit a reliable comparison family, so a pay percentile is not shown.
Why this analysis?
- This title does not yet fit a reliable comparison family, so a pay percentile is not shown.
- Salary confidence: High. The configured source supplied structured salary fields, a usable currency and a focused comparison value.
- Range quality: Focused salary range.
Employer compensation communication
Pay transparency at vCluster Labs
Very strong current pay transparency
This score uses the employer’s current visible listings and combines how often pay is disclosed with how useful those ranges are. Bonus, equity and benefit mentions are shown separately and do not raise the score.
This pattern comes from the employer’s current visible vacancies. It describes hiring and pay transparency in those listings, not employee satisfaction or a permanent judgement of the employer.
Current employer intelligence
vCluster Labs — current opportunity snapshot
Employer Evidence Profile
How often this employer’s current visible sampled vacancies state decision-critical information. These percentages describe evidence coverage, not employer quality.
Current sampled listings with advertised compensation evidence.
Current sampled listings whose work arrangement is clearer than unknown.
Current sampled listings with a supported country signal.
Current sampled listings with an explicit closing time.
Current sampled listings with a usable posting date.
Current sampled listings that explicitly indicate confirmed, possible or unavailable sponsorship evidence.
Current sampled listings with an explicit relocation signal.
Low coverage means the current visible listings state the information less often. It does not prove that the employer lacks the policy, benefit or support.
Common current occupation families: Sales (1) · Marketing (1) · Executive (1)
Visible seniority mix: Mid-career (1) · Senior / lead (1) · Leadership (3)
Current employment-type mix: Full time (6)
Other current roles from this employer
Head of Business Development, Inference Service Providers & AI Cloud Offtake
Remote — Worldwide
Leadership · Worldwide remoteSocial Media Manager
Remote — Worldwide
Seniority not clearly specified · Worldwide remoteVP, Global Growth Marketing
Remote — Worldwide
Leadership · Worldwide remoteDirector of HR
Remote — Worldwide
Leadership · Worldwide remoteThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
Current disclosed salary medians by currency
- USD 190,000 median · 5 disclosed salaries
Questions worth asking this employer
- If work authorization matters to you, what sponsorship policy applies to this specific role and location?
- If a move is required, is relocation assistance available for this position?
These questions are prompted by missing or thin evidence in the employer’s current visible vacancies. Missing evidence is not treated as a negative judgement.
This employer snapshot uses the employer’s current visible listings. Remote and sponsorship rates use only vacancies with explicit evidence, while missing information stays unknown. Salary medians are shown separately by currency and need at least five disclosed salaries. Zero confirmed sponsorship means none was explicitly found in this sample, not that sponsorship is unavailable.
This snapshot describes the employer’s current visible vacancies—things such as pay disclosure and work arrangement. It is not an employee-satisfaction or hiring-quality rating, and different currencies stay separate.
Work-location intelligence
Remote Freedom
Highly location-flexible
Why this score?
- The source describes the role as open worldwide or globally.
Flexibility signals detected
- Worldwide or global remote eligibility is explicitly indicated.
Remote Freedom measures observable location flexibility only. Unknown work-location information remains unscored. Timezone wording is penalized only when it appears restrictive; general collaboration across time zones is not treated as a restriction. A score does not guarantee legal work eligibility, payroll availability or visa sponsorship.
International applicant intelligence
Visa & relocation signals
Sponsorship status is shown only when the listing provides clear enough wording. Employer history or headquarters location is not used to guess an answer.
The available listing details do not contain a clear enough sponsorship statement.
The available listing details do not contain a clear enough relocation statement.
Tradeoff check
What’s the catch?
No obvious trade-off appears in the available job details. That does not mean the role has no drawbacks, so the original listing and employment terms are still worth reading carefully.
Application-path intelligence
What can we see about the application process?
Provider-mediated application path
The current application path comes through a publisher or aggregator. The destination may still lead to an employer-authorized hiring system, but that is not clear enough to assume.
Current destination: himalayas.app · HTTPS
No additional required application step is clear in the available listing text. This does not mean the external application is one-click or friction-free.
Application effort is estimated from visible listing and source details. Optional steps are kept separate from mandatory ones, and the external form may contain additional requirements that are not visible here.
Application safety context
Application safety check
Basic application-safety context available
The current application destination has a basic transport-safety signal such as HTTPS. This does not verify the employer, vacancy, recruiter or application process.
Evidence checked: Source provenance · Application destination · Listing wording
Observable transport-safety signals
- The available application destination uses HTTPS.
Before you share money or sensitive information
- Confirm the vacancy on the employer’s official careers site when practical, especially if a recruiter contacts you outside the listed application path.
- Check that recruiter email domains and application destinations are consistent with the employer or an identifiable recruiting provider.
- Do not pay application, processing, training or equipment fees merely to be considered for a job.
- Do not send cryptocurrency, gift cards, online-banking credentials or PINs as part of an application.
- Treat unusually fast offers or interviews conducted only through informal messaging channels as reasons to verify the employer independently.
This is a limited safety screen, not employer verification and not a fraud determination. Never send money, cryptocurrency, passwords or sensitive banking credentials merely because a listing appears on a job platform.
Original listing details
The section below comes from the listing source. The decision sections above use the job’s structured pay, location, qualification, mobility and application details to give you additional context.
As a Staff Network Engineer at vCluster Labs, you aren't just configuring switches; you are building the automation logic that configures them. AI Clouds run on InfiniBand and high-speed Ethernet fabrics that most teams still wire up by hand, one customer at a time. You will build the automation that turns that fabric into repeatable provisioning logic. You start in a small R&D group alongside our CTO and grow into owning this area as it becomes a core part of our platform.
As a Staff Network Engineer, your role will include:
Fabric automation: You will design and build the systems that automatically provision and configure NVIDIA switches and InfiniBand fabrics, including integration with NVIDIA UFM. Manual, per-customer switch setup is the thing you are replacing.
Network config management and sync: You will build the control loop that keeps switch, VLAN, and VXLAN state consistent with what our platform intends, detects drift, and reconciles it safely in production.
NAT gateway and L4 load balancing: You will build the gateway and load balancing layer that tenant clusters depend on for connectivity, with failover designed in from day one rather than bolted on later.
Scale and failure engineering: You will define how our network layer behaves at large scale: BGP route table limits, convergence, failover, and what happens when a link, switch, or gateway dies under real AI workloads.
Customer Zero for AI networking: You will run your automation on real AI Cloud environments, bring back what breaks, and turn hard-won operational lessons into product behavior our customers never have to think about.
Technical direction: You will help decide what we build versus integrate with partner solutions, write the design and requirements docs, and set the standards for how networking works across vCluster products.
This role could be a fit for you if you bring:
You have built network automation, not just operated networks: You have shipped software that configures switches, routers, or load balancers programmatically, ideally as part of a product or internal platform other teams relied on.
NVIDIA networking experience: Hands-on work with NVIDIA UFM, NVIDIA Spectrum or Quantum switches, Cumulus Linux, or NVUE, including programming against their APIs.
Deep fabric fundamentals: Strong command of InfiniBand, VLAN, VXLAN and EVPN, and BGP, including how they behave and fail at production scale.
Production scale scars: You have run networks at real production scale, seen them break, and helped fix the root cause with automation rather than runbooks.
Software engineering ability: You write production code in Go or Python, use version control and code review as a matter of course, and think of network config as code.
Bonus points for:
AI networking depth: Experience tuning fabrics for GPU training or inference workloads, such as RoCEv2, congestion control, rail-optimized topologies, or Spectrum-X.
AI Cloud or hyperscaler background: You helped build network automation at a GPU cloud, hyperscaler, or large CDN.
Load balancer and gateway internals: Experience building L4 load balancers or NAT gateways, including with eBPF/XDP or DPDK.
Open source: Contributions to networking or Kubernetes projects such as SONiC, FRRouting, Cilium, or MetalLB.
About vCluster Labs
We're the #1 platform for AI infrastructure, trusted by the world's fastest-growing AI cloud builders. We're a venture-backed startup that's raised over $28M from top-tier investors including Khosla Ventures (first investor in OpenAI, GitLab, Stripe, and DoorDash), and we're in a hyper-growth phase looking for motivated people to join our team. Our headquarters are in San Francisco (Salesforce Tower), but our team is distributed around the globe with a remote-first culture.
We give AI Cloud providers and AI factories a hyperscaler-like experience on their own GPU infrastructure. Our platform runs the full stack an operator needs, from bare metal provisioning and node lifecycle management up through managed Kubernetes, Slurm, Ray, and inference clusters, so they can turn raw GPUs into cluster products they can sell in days instead of spending 12+ months building it themselves. Today we power over 100,000 GPUs and 1 million CPUs across 50+ AI clouds and Fortune 500 companies, backed by a team of 40+ infrastructure engineers who build alongside our customers rather than just shipping them software.
We're the company behind vCluster, the open source technology for tenant isolation on Kubernetes, with 11,000+ GitHub stars and 40M+ tenant clusters created since 2021. Open source is part of our DNA. At KubeCon North America 2025, we launched our Infrastructure Tenancy Platform for AI, a Kubernetes-native framework built for running AI, ML, and GPU-intensive workloads anywhere, with an NVIDIA-validated reference architecture for DGX systems.
Benefits
We offer the following benefits:
Competitive Salary: We offer a competitive compensation package, including equity.
Premium Insurance: Health, dental, vision, and life Insurance, including plans for you and eligible dependents (benefits vary depending on country).
Flexible Working Schedule: You have a doctor’s appointment or need to head to the supermarket to get groceries at 2pm? We won’t have an issue with that. To us, results matter more than clocking in and out at the same time every day.
Workplace Flexibility: We’re very flexible about where you work. We know things can change in life and we’re happy to adjust the work environment for you along the way.
Culture & Values
At vCluster Labs, we value and stand for:
Make it Happen: We have a relentless bias for action and the grit to push through obstacles. We do whatever it takes to figure it out, put in the work, and ruthlessly prioritize the actions that drive measurable impact for the business.
Own the Outcome: We understand that our responsibility doesn't end when a task is checked off; it ends when the value is delivered. We connect our daily individual actions to the broader success of the company and our customers.
Create Wow: We measure success by the experience we generate, both inside and outside the company. For our customers, this means impressive speed and intuitive experiences. For our team, this means going the extra mile to support one another and to continuously drive each other to new heights.
Open Source, Open Mind: We are actively contributing to and maintaining open-source projects. Internally, we foster meritocracy — the strongest ideas win, no matter who or where they come from.
Build Tomorrow’s Standards, Intentionally: We don't just ship software; we define the state-of-the-art of tomorrow. We are fearless in tearing down old approaches to build something better, but we are disciplined in how we do it because we know our users rely on our technology to run mission-critical infrastructure platforms.
Compensation Range: $170K - $210K
Originally posted on Himalayas
Listing provenance
Where did this job come from?
See where this vacancy came from and whether more than one current source can still support it. Source names help with traceability and attribution; they are not endorsements or guarantees.
At least one enabled source recently observed the vacancy. The source chain is traceable, but this is not independent employer verification.
- Continuity
- One recent renewable source
- Source-class independence
- One renewable source class
- Last source observation
- Observed in the current source window
This records when High Paid Job last observed the vacancy in source evidence. It confirms source presence, not that the employer edited the vacancy at that time.
- 1 enabled source recently observed this vacancy.
Source confidence is about traceability and continuity. It is separate from application safety and should not be read as an employer reputation rating.
The vacancy is supplied by an external job publisher. Source information helps show where the listing came from; it is not a guarantee about the employer or vacancy.
Listing source: Himalayas. Destination: himalayas.app. The application opens in a new tab so you can keep this report open.
