Job intelligence
GTM AI Engineer
Customer.io
Before relying on the listing: Confirm Application closing time with the employer or source. See verification questions
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
This opportunity needs a closer read before drawing a strong conclusion, especially around the salary benchmark is still shallow.
The range is usable, but the comparable sample is still too shallow for a strong relative-pay call.
Geographic eligibility is restricted to a country or region.
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
4 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
- Location eligibility
- Employment type
What to verify next
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
Unknown information is never converted into a negative score. The questions above exist to prevent missing evidence from being mistaken for a favorable term.
Decision levers
What could make or break the fit?
Reasons to look closer
Nothing stands out strongly enough yet to call a clear advantage. The role may still be attractive for reasons the listing does not spell out.
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.
- Location rules could change the fit: Geographic eligibility is restricted to a country or region.
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.
Opportunity neighborhood
Keep your options open
These live roles sit close enough to this opportunity to make useful comparison points. Look across several employers before deciding what pay, flexibility or access trade-offs you are willing to accept.
Machine Learning Engineer, New Grad - Quora
Quora · Canada, USA
Why it is nearby: Same country · Similar work arrangement · Same employment type
About 16% lower advertised midpoint
Different angle: Seniority is not explicit
Data Scientist
Citizenship and Immigration Services · Camp Springs, Maryland
Why it is nearby: Same country · Recently posted
About 52% lower advertised midpoint
Different angle: Seniority is not explicit
Data Scientist (Data Management)
Immigration and Customs Enforcement · Fairfax, Virginia
Why it is nearby: Same country · Recently posted
About 10% lower advertised midpoint
Different angle: Seniority is not explicit
Analytics Engineer, Data
Tailscale · Canada
Why it is nearby: Similar work arrangement · Same employment type · Recently posted
Different angle: Seniority is not explicit · Different country
This neighborhood is drawn from current inventory in the same broad occupation. Similarity is based on explicit listing facts; missing details do not count against a job.
Role market context
How much current choice is visible around this kind of work?
This compares the vacancy with current High Paid Job inventory in the broad Data & AI roles family. It describes visible choice and disclosure, not future demand or career quality.
200 most recent current roles sampled for the disclosure measures below.
Distinct employers in the bounded current sample, not an estimate of all employers hiring in the market.
Current sampled roles stating at least four of the five Core Decision Facts.
Requires a numeric amount, explicit ISO currency and supported pay period.
Listings with explicit enough remote, hybrid or on-site evidence to classify.
Missing deadline evidence remains unknown and is not interpreted as an open-ended application window.
Currencies with explicit pay evidence in the sample: USD (27) · EUR (12) · GBP (5) · CAD (2). Raw amounts across different currencies are not compared.
This describes current visible High Paid Job inventory in the same broad occupation family. Percentages use a bounded recent sample and are not a forecast, a complete labor-market census or an employer-quality measure.
Constraint opportunity lab
What changes the size of the current opportunity pool?
Each line applies one stricter evidence-based constraint to the same bounded current role-family sample. It helps you see the trade-off in visible choice without deciding which trade-off is right for you.
Counts only affirmative or possible sponsorship evidence, or relocation explicitly offered. Unknown is not treated as no.
A much stricter subset: only listings with explicit worldwide-remote evidence remain.
Shows the subset with enough stated evidence for a more informed first comparison.
Requires amount, explicit ISO currency and a supported pay period. Missing pay evidence remains unknown.
Counts roles explicitly classified as worldwide remote, region-restricted remote or remote with restrictions still unclear.
Uses only roles where a country is known. Roles without country evidence are excluded from this denominator.
Includes roles whose seniority is genuinely unspecified rather than assuming they belong to another level.
Only same-currency opportunities with usable annualized pay enter this comparison. Other currencies are not converted or treated as lower.
These are counterfactual filters over a bounded sample of current HPJ inventory in the same broad occupation family. They show how visible choice changes when one evidence-based constraint is applied; they do not tell you which constraint you should choose or predict hiring outcomes. The calculation uses the 200 most recent current roles from 1083 visible roles in this broad family.
Salary transparency context
Is pay disclosure typical for this kind of role?
This listing states usable structured compensation. About 24% of the bounded current role sample does the same.
Compensation counts only when amount, ISO currency and supported pay period are all known.
Pay disclosure is uncommon in the current role sample.
This employer’s current visible listings disclose pay materially more often than the current same-role sample.
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, current same-currency market context, 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
- Is there a bonus, commission or other variable-pay component, and how is it calculated?
- What retirement or pension contribution does the employer provide?
- 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?
- Is there a firm application deadline, a rolling review window or no stated closing date?
Occupation intelligence
What broader career references connect to this role?
HPJ uses broad comparison families for current-market analysis. External taxonomy results are reference candidates for that broad family, not a declaration that this vacancy has been authoritatively classified into a specific occupation.
European occupation references
This service uses the ESCO classification of the European Commission.
U.S. occupation references
- Data Scientists 15-2051.00
- Computer and Information Research Scientists 15-1221.00
- Social Science Research Assistants 19-4061.00
- Atmospheric and Space Scientists 19-2021.00
- Bioinformatics Scientists 19-1029.01
This site incorporates information from O*NET Web Services by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). O*NET® is a trademark of USDOL/ETA.
Career reference research
Skills worth investigating
Official occupational context, paired with exact phrases visible in this vacancy. It is not a skills test or an applicant-fit score.
ESCO · European occupation
data scientist
Usually essential in this ESCO occupation
- statistical modeling techniques
- perform project management
- query languages
- online analytical processing
- develop data processing applications
- data engineering
- manage data collection systems
Context-dependent ESCO skills
- manage ICT data architecture
- SPARQL
- use spreadsheets software
- computational biology
- state estimation
O*NET · U.S. occupation
Data Scientists
O*NET occupation skills
- Mathematics
- Critical Thinking
- Reading Comprehension
- Complex Problem Solving
- Programming
- Active Learning
- Speaking
- Active Listening
Build my private skill preparation brief Your evidence · Practice · Interview questions
Plan how you might demonstrate or investigate occupational skills. These are broad-family reference examples, not confirmed vacancy requirements. Nothing you enter is sent to High Paid Job.
Private to this browser. Up to 20 reference skills; not a qualification assessment or hiring prediction.
Useful next question: Which of these occupational reference skills does the hiring manager actually expect for this specific role, and what evidence would demonstrate them?
These skills belong to one reference occupation selected for HPJ’s broad career family, not a verified classification of this vacancy. Text overlap only means a phrase appears in the available listing text; it does not establish an employer requirement, your proficiency, or a qualification gap. A missing mention is unknown, not a deficit.
Adjacent current roles to investigate
Vulnerability Research Software Engineer
Socket · Canada, USA
same stated country · same employment type · similar work-arrangement evidenceForward Deployed Product Manager, AI Agent
Cresta · USA
same stated country · same employment type · similar work-arrangement evidenceSenior Product Manager
Rithum · USA
same stated country · same employment type · similar work-arrangement evidenceAdjacent-family roles are exploration prompts from current HPJ inventory. They are not inferred qualification matches and they do not imply a promotion path.
Career move map
What sits one step away?
This listing is currently read as Leadership. Nearby roles one visible seniority step away can help you judge whether to widen the search, stretch upward or compare the responsibilities more carefully.
Broader-entry direction
Staff Machine Learning Engineer, Recommendation Systems - Quora
Quora · Canada, Ireland, USA
USD 219,989–320,613 / year Same country · Similar work arrangement · Same employment type Advertised midpoint is about 74% higherInstructor, AI/Machine Learning, Simplilearn (Part time)
Fullstack Academy · USA
USD 100,000–110,000 / year Same country · Similar work arrangement · Recently posted Advertised midpoint is about 32% lowerThese are live roles one visible seniority step away in the same broad occupation family. They can reveal nearby options, but they are not a guaranteed promotion path and do not account for your personal experience.
Skill bridge
What does this role connect to?
Google Cloud is one of the signals this listing shares with skills appearing often across current Data & AI roles opportunities.
Skills named in this listing
Shared with the current career sample
- Google Cloud Seen in 20 sampled listings
- Kubernetes Seen in 12 sampled listings
- Large Language Models Seen in 37 sampled listings
Application edge
- If these skills match your background, prepare one concrete example that shows how you used Google Cloud, Kubernetes, and Large Language Models rather than relying on a keyword-only claim.
- The listing mentions extra application steps. Review those requirements before starting so you can prepare the requested material in one pass.
If the named skills are genuinely transferable in your own experience, the occupation map also points to adjacent current families worth researching: Software engineering roles and Product roles. This is exploration context, not a qualification match.
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. The current career comparison draws on 120 sampled listings; 117 contain a recognized skill signal.
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.
Google Cloud
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.
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.
Large Language Models
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.
Prepare for a stated application step
A background or pre-employment screening step is explicitly mentioned.
Questions worth resolving before you rely on the opportunity
- Application closing time: Is there a firm application deadline, a rolling review window or no stated closing date?
- Work authorization / sponsorship: If sponsorship or work authorization matters to you, what exact immigration or employer-sponsorship conditions apply to this role?
Decision analysis
What the listing really tells you
A closer look at GTM AI Engineer at Customer.io points most strongly to pay is visible, but the benchmark is still thin, remote flexibility can be weighed properly, and the visible application effort can be estimated. Those signals shape the practical upside and the questions still worth asking.
Pay is visible, but the benchmark is still thin
The USD range can be compared directly within its currency, although the present comparison sample is too shallow for a confident relative-pay ranking.
Remote flexibility can be weighed properly
Location flexibility can be assessed here: Remote with some uncertainty or restrictions, with a Remote Freedom reading of 62/100. One practical limit to notice is geographic eligibility is restricted to a country or region..
The visible application effort can be estimated
Provider-mediated application path · 1 visible process step. The external application may contain additional steps that are not visible from the listing itself.
The listing can be traced to a current source
The opportunity currently has 1 renewable source path across 1 source classes. Multiple independent paths can strengthen continuity, but they are not a substitute for checking the application destination.
How this analysis is assembled
Built from the pay, location, qualification, mobility, application and source details available for this vacancy. Anything the listing leaves unresolved stays unresolved.
Analysis evidence coverage
How much analysis can the current evidence support?
Only 6 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
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 source posting date is today.
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
No standout strength is supported strongly enough to list here. That is not a negative rating.
Visible cautions
- Geographic eligibility is restricted to a country or region.
- The role may involve non-standard hours or on-call work.
- This is remote work with a geographic restriction, not a worldwide-remote vacancy.
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.
1 explicit Remote Freedom restriction signal is present and is shown separately from qualification requirements.
- 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.
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 source posting date is today.
Compensation intelligence
How competitive is this pay?
Only 6 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
Why this analysis?
- Only 6 comparable salary observations are available. At least 10 are needed before showing a High Pay Score.
- 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 Customer.io
Good 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
Customer.io — 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: Finance Accounting (3) · Sales (3) · Data & AI (2)
Visible seniority mix: Senior / lead (5) · Leadership (7)
Current employment-type mix: Full time (16)
Most visible hiring countries in this sample: United States (6) · United Kingdom (1)
Other current roles from this employer
Global Controller
LATAM, Canada, USA
Leadership · Region-restricted remoteUSD 250,000–280,000 / yearEngineering Manager
LATAM, Canada, USA
Leadership · Region-restricted remoteUSD 185,000–215,000 / yearMid-Market Account Executive, EMEA
EMEA
Leadership · Region-restricted remoteUSD 95,000–190,000 / yearSenior Software Engineer, Backend
EMEA
Leadership · Region-restricted remoteUSD 150,000–200,000 / yearThese are other current vacancies visible from the same employer, not endorsements or evidence of future hiring plans.
Current disclosed salary medians by currency
- USD 165,000 median · 12 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?
- What is the expected application and interview timeline if the listing does not state a closing date?
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
Remote with some uncertainty or restrictions
Why this score?
- The role is remote but the source identifies a country or regional restriction.
Location restrictions detected
- Geographic eligibility is restricted to a country or region.
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?
These are visible conditions worth checking before treating the headline compensation as the whole story:
- The role may involve non-standard hours or on-call work.
- This is remote work with a geographic restriction, not a worldwide-remote vacancy.
Current alternatives
Better-paying alternatives
These current roles show a materially higher annualized salary midpoint in the same broad occupation and currency. Similar seniority, country, work arrangement, employment type and recency are preferred where possible; higher pay alone does not make an alternative a better fit.
Director of Product, Machine Learning & Decisioning Platforms
Upstart · Canada, USA
USD 216,100–299,000 / year Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
Senior Pricing Data Scientist
Fivetran · USA
USD 209,378–261,723 / year Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
Senior Data Scientist, Audio
Deepgram · USA
USD 178,000–220,000 / year Region-restricted remoteWhy comparable: Same seniority band · Same country · Similar work-location arrangement
Alternatives are drawn from the current inventory rather than presented as application recommendations. A pay difference needs to be meaningful—about 3% or more at the midpoint—and different currencies are not compared.
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: jobicy.com · HTTPS
Visible application steps or requirements
- A background or pre-employment screening step is explicitly mentioned.
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.
About Customer.io
Over 9,000 companies — from scrappy startups to global brands — use our platform to send billions of emails, push notifications, in-app messages, and SMS every day. Customer.io powers automated communication that people actually want to receive. We help teams send smarter, more relevant messages using real-time behavioral data.
About the role
Hi, my name is Nick Guardino, Senior Director of Marketing Ops at Customer.io, and I'm looking for a GTM AI Engineer to help take our AI agents from scrappy prototypes to production-grade systems our GTM teams can depend on.
Over the last 3.5 months, our GTM AI team has built 11 agents now running in production, serving 120 active users and roughly 25,000 tool calls a day — all through custom CLIs that work, but weren't built to scale. We believe businesses can run leaner and go further when they deploy AI agents well, and we're figuring out that motion in real time. This role owns the scale and reliability layer so the rest of the team can keep building.
What we value
- Craft over quick wins — energized by making things robust, not just making them work.
- A point of view — we want someone who asks "why did you build it that way?" and has a specific answer for what to do instead.
- Comfortable being wrong — you try things fast, and you course-correct just as fast.
- AI-native by default — you'd rather direct Claude to write and QA code than write it by hand.
What you'll do
- Alpha-to-production ownership — take newly built agents from working v1 to production-ready: write evals, harden prompts and tool definitions, and refactor prototype scaffolding into clean, production-quality code.
- Observability & stability — instrument tracing, logging, and monitoring across the agent fleet so we catch regressions before our 120+ GTM users do.
- Deployment & infrastructure — stand up and maintain the pipelines that get agents into users' hands without surprises, owning environment parity and release hygiene on our GCP stack.
- Database administration — own how agents read from and write to our databases, safely and at scale.
- Fleet maintenance — monitor agent behavior in production, triage issues, and ship the steady stream of improvements that make an agent indispensable rather than just useful.
- Partner closely with the GTM AI team — free up our agent builders to stay in their zero-to-one wheelhouse while you own scale and reliability.
- Bring an outside point of view — tell us what we built wrong, and back it up with a plan to fix it.
What we're looking for
- 4+ years in software engineering, platform/infrastructure engineering, or a similarly technical role, ideally at a B2B SaaS company.
- Comfort working in the terminal daily, with a real GitHub PR-and-deploy workflow.
- Cloud hosting experience — Kubernetes, VMs, or equivalent; Google Cloud experience strongly preferred.
- Experience with how agents interact with and edit databases, including some hands-on database administration.
- Familiarity with LLM-based application development: prompt engineering, tool/function calling, evals, and modern agent frameworks.
- Ability to prompt AI tools correctly, review their output critically, and direct them to QA their own work — this is an AI-native role, not a hand-coding one.
- Scrappy enough to iterate fast, disciplined enough to think about consistency once something needs to scale.
- A point of view, and the willingness to ask "why did you build it that way?"
Compensation & Benefits
We believe in transparency. Starting salary for this role is $140,000–$170,000 USD (or equivalent in local currency) depending on experience and subject to market rate adjustment. In addition to base salary, this role includes an equity grant in the form of stock options, so you share in the success you help build.
We know our people are what make us great, and we’re committed to taking great care of them. Our inclusive benefits package supports your well-being and growth, including 100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family. We also offer 16 weeks paid parental leave, unlimited PTO, stipends for remote work and wellness, a professional development budget, and more.
Our Process
No gotchas, no trick questions - just a clear, human process designed to help both of us make an informed decision.
- 30-minute Zoom call with Recruiter
- 45-minute Zoom call with Hiring Manager
- 45-minute Zoom call with a member of the GTM AI team
- 60-minute Live technical session with the team
All final candidates will be asked to complete a background check and employment verifications as part of our pre-employment process.
Customer.io recognizes the stifling impact of systemic injustice on diverse communities. We commit to using our influence to increase inclusion and equity within the tech industry. We strive to build an inclusive team culture, implement bias-free hiring practices, and develop community partnerships to expand our global impact.
Zoom is the only video conference platform that we use, virtual interviews will be conducted using the video capability (i.e., not via the chat), and offers will be extended in writing on official Customer.io letterhead. Please be vigilant in all of your job search activity, and if you have any questions please contact jobs@customer.io.
Join us!
Check out our careers page for more information about why you should come work with us! We believe in empathy, transparency, responsibility, and, yes, a little awkwardness. If you’re excited by what you read — apply now.
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 very recently
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: Jobicy. Destination: jobicy.com. The application opens in a new tab so you can keep this report open.