Location: San Francisco; New York City
In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people and teams adopt Perplexity and Computer on their own, and the Growth team owns the loops that turn that adoption into lasting usage and revenue.
We're hiring a Growth GTM Engineer to build the systems that turn product usage into revenue and turn self-serve usage into enterprise pipeline. You'll turn first-party Computer and Enterprise usage into account-level signals. You'll ship the in-product paths that capture sales intent, and build and validate those signals with data science. Alongside product engineers, you ship production code, instrument the product and run experiments. You'll partner closely with Revenue Operations, who own Salesforce, CPQ, routing and sales reporting.
Tech Stack: TypeScript | Next.js | React | Python | PostgreSQL | Snowflake | Eppo | AWS
WHY PERPLEXITY IS DIFFERENT
- Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious.
- Ownership. You identify the problem, design the solution and ship it.
- Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users.
- Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products.
- Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence.
WHAT YOU'LL DO
- Build account-level PLG signals: map users and workspaces to accounts, and define the activation, expansion and intent signals that predict an enterprise deal. Publish them as trusted models that sales use for scoring and routing.
- Own the in-product paths from self-serve to sales, like contact-sales entry points, high-intent upsells and meeting booking, across web and app. Decide who sees them, when and with what context, and measure them end to end, from surface to booked meeting to pipeline.
- Lead experiments end to end on sales-assist surfaces and targeting, from hypothesis and instrumentation through analysis and rollout. Partner with Data Science to measure meetings and qualified opportunities, not just clicks.
- Build the internal tools and automation Growth and GTM teams run on
- Partner closely with Sales, Sales Systems, Data Science, Marketing and Product to turn product signals into pipeline. Be upstream partner to sales systems that own Salesforce, CPQ and routing
QUALIFICATIONS
- 2+ years as a growth, GTM, data or full-stack engineer, shipping production code (TypeScript/React, Python).
- Strong SQL and comfort building data models in a warehouse (Snowflake, dbt-style).
- Experience instrumenting product events and running A/B experiments end to end.
- Commercial instinct: you start from a revenue problem ("trial-to-enterprise conversion won't move") and work back to the signal or surface that fixes it.
- Comfort with REST APIs, webhooks and integrating third-party GTM tools.
- Operator mindset: you talk to customers directly, ship fixes, and don't need a PM to translate requests.
NICE TO HAVE
- Experience in a PLG-to-enterprise motion: product-qualified leads, scoring users into accounts, sales-assist flows.
- Experience as a GTM or growth engineer at a B2B SaaS or GTM-tooling company.
- Entity resolution, dedup or domain enrichment.
- Familiarity with Salesforce, Default, Chili Piper, Intercom, Clay, Hightouch/Polytomic or similar (as a consumer and integrator, not an admin).
- Experience building LLM-powered internal tools or agents.
Location: New York
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
The GTM Strategy & Operations is on Harvey’s Revenue Operations team focused on our overlay organizations: Customer Success, Legal Engineering, and adjacent post‑sale teams.
This team serves as a core strategic and operational partner to GTM, helping these overlays scale their impact across the customer lifecycle. In this role, you act as a strategic force multiplier and trusted advisor to overlay leaders, helping them sharpen strategy, tighten execution, and focus on the highest‑leverage work.
You will spend your time partnering with these leaders, driving cross‑functional initiatives that support them, and building the operating rhythms that keep overlays and core sales aligned.
It is an opportunity to sit close to customer‑facing decisions, influence how our overlay orgs evolve, and help define what “great” looks like for Harvey’s go-to-market engine.
WHAT YOU'LL DO
- Partner closely with overlay GTM leaders (e.g., Customer Success, Legal Engineering and related teams) to shape strategy, refine existing processes, and optimize execution across their organizations, bringing a clear point of view on where to focus.
- Act as a business partner to these overlay teams, helping establish and evolve the strategic and operational foundations for how they plan, execute, and measure success in support of our broader GTM goals.
- Drive Rhythm of the Business rigor and scalability for overlays by implementing and running operating processes and cadences (e.g., portfolio reviews, planning cycles, business reviews) that enable structured, repeatable growth.
- Define, scope, and drive high‑priority initiatives that address complex, high‑impact problems for Customer Success and Legal Engineering, from opportunity identification through execution and follow‑through.
- Work cross‑functionally with Sales, Customer Success, Legal Engineering, RevOps, Finance, and Product to align on goals, clarify roles between overlays and core teams, and ensure programs land cleanly in the field.
- Translate qualitative and quantitative insights from overlay and field stakeholders into clear recommendations for GTM leadership, focusing on strategic trade‑offs, resourcing, and process improvements rather than pure analytics.
WHAT YOU HAVE
- 4+ years of experience in Revenue Operations, GTM Strategy & Operations, consulting, or finance. Ideal candidates will have a combination of GTM Strategy & Operations experience in a high‑growth B2B or SaaS environment, and experience in investment banking, private equity, venture capital, strategy / management consulting, or other highly analytical roles.
- Demonstrated ability to be an effective business partner; you build trusted relationships, navigate different working styles, and influence without direct authority.
- Strong cross‑functional collaboration skills; you are energized by working across Sales, Customer Success, Legal Engineering, and other teams and can bring people together around shared goals and clear operating plans.
- Comfort with structured problem solving and making recommendations in ambiguous or undefined areas, even when inputs from overlay and core teams are imperfect or incomplete.
- Bias toward action and ownership; you enjoy rolling up your sleeves, driving initiatives from 0→1, and iterating based on feedback from GTM and overlay stakeholders.
- Clear written and verbal communication skills, with the ability to frame trade‑offs, articulate rationale, and align GTM and overlay leaders around decisions.
COMPENSATION
$136,000 - $204,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-TM1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: Canada
About Improvado
Improvado is a marketing data and AI analytics platform for enterprise brands and agencies. We connect 500+ marketing and sales data sources, normalize them through a governed data model, and put an AI agent on top so marketing teams can ask questions of their own data without going through BI or IT.
What we sell:
extraction and 500+ connectors; data transformation (SQL and dbt-compatible); Marketing Data Governance — taxonomy, naming, data-quality rules; warehouse and storage; dashboards; AI agent and MCP access to live marketing data; DECS, data engineering as a service on a 2 to 4 week SLA.
Who buys it:
Economic buyers:
CMO, VP Marketing, VP Demand Gen, agency COO and ops leadership
Technical evaluators:
VP or Director of Marketing Analytics, marketing analysts, data engineering, sometimes IT and security
Segments:
enterprise brands, mid-market, agencies
Verticals:
pharma and healthcare, financial services, retail and eCommerce, gaming, agencies
Why this role, now
Our messaging is not aligned.
Positioning, web, sales pitch, product and content each carry a different version of what Improvado is. The market categorizes us as "marketing ETL" while we position as an AI marketing analytics platform. That gap costs us deal quality and price.
The category is crowded and moving fast.
Battlecards exist but decay, and nobody owns keeping them true.
Attribution, incrementality and causal measurement is where deals are won and lost
— and it is the hardest thing to argue credibly without hand-waving.
Analyst firms are a silent blocker.
When an enterprise buyer asks Gartner or Forrester about Improvado, there is no briefed narrative waiting for them.
You would not start from a blank page. We already have a positioning registry, roughly 11 documented buyer personas, a pain-point and value-prop library, competitor intel reports and about 10 battlecards. They are inconsistent and under-used. Your first job is to make one version true and make people use it.
What you'll own
Positioning and messaging.
Core positioning, category framing and message hierarchy across ICPs and personas. ICP and persona documentation that is used, not filed. The messaging layer of new product and feature launches, including the internal rollout that makes the field able to sell it.
Competitive intelligence and win/loss.
A structured win/loss interview program with quarterly readouts. Living battlecards. Monitoring competitor positioning, pricing and product moves, and driving our counter-positioning.
Sales enablement.
The core pitch narrative, demo storyline and objection-handling framework. The messaging components of new-rep onboarding. A standing weekly cadence with Sales leadership — not quarterly check-ins. Direct support on competitive and enterprise deals: RFPs, security and technical evaluations, displacement plays.
Market and analyst relations.
The Improvado narrative for Gartner, Forrester and category influencers, so that a buyer's analyst call becomes an accelerator rather than a blocker. Feeding structured market and buyer insight back into product prioritization.
What we're looking for
4 to 8 years in product marketing, or an equivalent blend of product marketing with marketing analytics, marketing or data ops, sales engineering, analytics consulting, or product management on a data product.
Category fluency in marketing data and measurement: attribution models, incrementality testing, MMM, data governance and taxonomy, warehouses and ETL/ELT — including where each is honestly weak.
B2B SaaS sold to marketing or data buyers. Marketing analytics, martech, measurement, CDP, BI and data-infrastructure vendors are the reference profile.
Proof you have shipped, not just documented: positioning that changed the website and the pitch, battlecards reps actually opened, a win/loss program that survived past its second quarter.
Writing that survives contact with a skeptical technical buyer — claim and evidence, not adjective stacking.
Comfort operating close to Sales: weekly cadence, deal reviews, live calls, direct feedback.
Nice to have:
hands-on SQL, dbt or BI, enough to validate a claim yourself. Experience marketing AI capabilities without hype. Analyst-relations experience. Agency-side or enterprise-brand background. Vertical depth in pharma and healthcare, financial services, retail and eCommerce, or gaming.
Not a fit if:
your product marketing has been mostly launch logistics and content calendars; you need a fully staffed team and a finished brand system to be effective; you are uncomfortable being told in a deal review that your messaging did not work.
How we measure success
Win rate in competitive deals against our top 3 named competitors, baseline set in month 1.
Stage-to-stage conversion on open opportunities, particularly discovery to demo to proposal.
Time-to-first-deal for new reps.
Field adoption of enablement assets — measured, not assumed.
Win/loss program running on cadence, with themes that visibly change product and GTM decisions.
Message consistency: a quarterly audit across web, deck, product UI and content.
What We Offer
Remote-first environment
Strong product/market fit: marketing data product for US-based enterprises
20 working days of PTO per year
US holidays and additional days off
Professional development reimbursement
Location: San Jose, California, United States
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles:
We Before Me
,
Do the Right Thing
, and
Get Things Done
. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.
About the Opportunity
We are seeking a Model Risk Director focused on Fraud and AI to join OKX’s Model Risk Management (MRM) function. As a senior member of the second line of defense (2LOD), this leader will provide independent oversight and effective challenge of fraud models used to detect, prevent, and manage fraud risk across OKX’s products and customer journeys.
The role will lead end-to-end validation of fraud models, from conceptual soundness, data and implementation review to outcomes analysis, performance monitoring, and remediation follow-up. The portfolio may include supervised machine learning models, anomaly detection, graph and network analytics, rules-based or hybrid systems, and AI-enabled fraud applications.
The ideal candidate brings deep hands-on experience in fraud model validation, strong quantitative judgment, and practical experience assessing AI/ML models. This person will partner closely with Fraud, Risk, Product, Data Science, Engineering, Compliance, and Audit teams while maintaining the independence of the MRM function.
This is a hands-on, builder role: the successful candidate will independently establish the fraud model validation capability from the ground up, personally execute validations, and play a leading role in assessing AI-enabled systems.
What You’ll Be Doing
Establish and own the independent validation framework for fraud models and AI-enabled decision systems across OKX products, covering conceptual soundness, data quality, implementation, and outcomes analysis, in line with SR 26-2 and equivalent model risk frameworks.
Assess model conceptual soundness, intended use, assumptions, and limitations.
Personally execute end-to-end model validations as the technical expert, including independently reproducing results through hands-on data analysis and code review.
Assess AI/ML and generative AI applications, including LLM-based and agentic systems, for robustness, reliability, explainability, and appropriate human oversight, applying strong applied AI evaluation expertise.
Perform ongoing monitoring review and periodic revalidation to ensure sustained model performance through changing fraud patterns and business conditions.
Provide effective challenge to model owners; communicate conclusions, limitations, and risk ratings clearly to senior management and governance forums, and track remediation through closure.
Build and continuously mature the fraud model validation capability, standards, and workflows within MRM.
What We Look For In You
Master’s or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, or a related discipline, or equivalent experience.
10+ years of quantitative, fraud risk, or model risk experience, with a recognized track record as a hands-on technical expert who personally delivers independent validations of models and decision systems.
Excellent communication and judgment, including the ability to explain quantitative findings to senior audiences and constructively challenge model owners.
Practical experience with statistical and machine learning methods; proficiency in Python and SQL; working knowledge of SR 11-7 or equivalent model risk and AI governance frameworks.
Experience with AI/ML governance and controls, including explainability, fairness, robustness, ongoing monitoring, or generative and agentic AI applications in fraud operations.
Nice to Haves
Experience establishing validation frameworks, methodologies, or capabilities in settings where they did not previously exist.
Strong applied AI capability: hands-on experience evaluating or building ML/LLM-based systems in production, including prompt engineering, evaluation harnesses, fine-tuning assessment, or agentic AI workflows; able to run red-team style testing on AI applications.
Perks &
Benefits
Competitive total compensation package
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!
OKX Statement:
OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
The salary range for this position is $200,000 - $300,000
The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site.
Notice:
All official
OKX
vacancies are published on this website.
While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated.
If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to
OKX
's
Candidate Privacy Notice
.
Location: New York, United States
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles:
We Before Me
,
Do the Right Thing
, and
Get Things Done
. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.
About the Opportunity
We are seeking a Model Risk Director focused on Fraud and AI to join OKX’s Model Risk Management (MRM) function. As a senior member of the second line of defense (2LOD), this leader will provide independent oversight and effective challenge of fraud models used to detect, prevent, and manage fraud risk across OKX’s products and customer journeys.
The role will lead end-to-end validation of fraud models, from conceptual soundness, data and implementation review to outcomes analysis, performance monitoring, and remediation follow-up. The portfolio may include supervised machine learning models, anomaly detection, graph and network analytics, rules-based or hybrid systems, and AI-enabled fraud applications.
The ideal candidate brings deep hands-on experience in fraud model validation, strong quantitative judgment, and practical experience assessing AI/ML models. This person will partner closely with Fraud, Risk, Product, Data Science, Engineering, Compliance, and Audit teams while maintaining the independence of the MRM function.
This is a hands-on, builder role: the successful candidate will independently establish the fraud model validation capability from the ground up, personally execute validations, and play a leading role in assessing AI-enabled systems.
What You’ll Be Doing
Establish and own the independent validation framework for fraud models and AI-enabled decision systems across OKX products, covering conceptual soundness, data quality, implementation, and outcomes analysis, in line with SR 26-2 and equivalent model risk frameworks.
Assess model conceptual soundness, intended use, assumptions, and limitations.
Personally execute end-to-end model validations as the technical expert, including independently reproducing results through hands-on data analysis and code review.
Assess AI/ML and generative AI applications, including LLM-based and agentic systems, for robustness, reliability, explainability, and appropriate human oversight, applying strong applied AI evaluation expertise.
Perform ongoing monitoring review and periodic revalidation to ensure sustained model performance through changing fraud patterns and business conditions.
Provide effective challenge to model owners; communicate conclusions, limitations, and risk ratings clearly to senior management and governance forums, and track remediation through closure.
Build and continuously mature the fraud model validation capability, standards, and workflows within MRM.
What We Look For In You
Master’s or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, or a related discipline, or equivalent experience.
10+ years of quantitative, fraud risk, or model risk experience, with a recognized track record as a hands-on technical expert who personally delivers independent validations of models and decision systems.
Excellent communication and judgment, including the ability to explain quantitative findings to senior audiences and constructively challenge model owners.
Practical experience with statistical and machine learning methods; proficiency in Python and SQL; working knowledge of SR 11-7 or equivalent model risk and AI governance frameworks.
Experience with AI/ML governance and controls, including explainability, fairness, robustness, ongoing monitoring, or generative and agentic AI applications in fraud operations.
Nice to Haves
Experience establishing validation frameworks, methodologies, or capabilities in settings where they did not previously exist.
Strong applied AI capability: hands-on experience evaluating or building ML/LLM-based systems in production, including prompt engineering, evaluation harnesses, fine-tuning assessment, or agentic AI workflows; able to run red-team style testing on AI applications.
Perks &
Benefits
Competitive total compensation package
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!
OKX Statement:
OKX is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
The salary range for this position is $200,000 - $300,000
The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered. Applicants should apply via OKX internal or external careers site.
Notice:
All official
OKX
vacancies are published on this website.
While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated.
If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to
OKX
's
Candidate Privacy Notice
.
Location: United States, San Mateo, CA
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Staff Software Engineer, Data Governance & Trust
San Mateo, CA
About the role
Sony Interactive Entertainment is seeking a Staff Software Engineer to help shape and deliver the technical foundation for Data Governance and Trust across our data and AI ecosystem.
Our ambition is to make data understandable, reliable, reusable, and appropriately governed for the people, applications, and AI systems that depend on it. Achieving this requires shared platform capabilities, clear ownership, and governance practices embedded into how teams build and operate data products.
In this role, you will establish technical direction, lead initiatives across teams, and remain hands-on in architecture and implementation. You will connect metadata, lineage, data quality, semantic context, and policy controls into practical capabilities that help teams use data with confidence.
You will also be a trusted technical representative for the Data Governance and Trust group. We are looking for someone who can lead productive discussions, explain complex tradeoffs, navigate difficult conversations, and build alignment across engineering, business, governance, security, and privacy stakeholders.
This is an individual contributor leadership role with impact across teams.
What you will do
Set technical direction and deliver shared capabilities
Shape the architecture and technical roadmap for Data Governance and Trust in partnership with engineering leadership, product partners, domain teams, and governance stakeholders.
Lead initiatives from discovery and ambiguous requirements through design, implementation, adoption, and ongoing operation.
Design and build services, integrations, APIs, and automation that connect metadata, ownership, classification, lineage, quality signals, and policy information across the data ecosystem.
Establish reusable engineering patterns that embed trust requirements into data publishing, discovery, access, consumption, change, and retirement.
Stay hands-on through prototypes, production code, design reviews, and the resolution of complex technical problems.
Lead conversations and build alignment
Serve as a technical spokesperson for the group in architecture discussions, planning forums, domain engagements, and leadership reviews.
Facilitate discussions among stakeholders with different priorities, surface disagreements constructively, and guide decisions toward clear outcomes.
Explain technical choices, business implications, risks, and costs to both engineering and nontechnical audiences.
Challenge assumptions respectfully, incorporate feedback, and help teams reach workable agreements on standards, ownership, and implementation.
Document decisions, clarify responsibilities and dependencies, and follow through on commitments across teams.
Build relationships that enable adoption through credibility, collaboration, and influence.
Make governance practical and sustainable
Partner with governance, security, privacy, and domain stakeholders to translate agreed requirements into implementable controls and traceable evidence.
Help domain teams define data contracts, quality expectations, ownership responsibilities, and lifecycle practices supported by shared platform capabilities.
Connect quality and reliability signals to accountable owners, consumer communications, and remediation workflows.
Evaluate build, buy, and integration choices based on interoperability, usability, reliability, operating cost, and long-term flexibility.
Measure success through improvements in approved data use, adoption, reliability, reuse, and operational effort.
Prepare the foundation for AI consumption
Develop ways to make business meaning, provenance, quality status, and permitted-use information available to applications and AI through supported interfaces.
Partner with AI and platform teams on governed access to data and context, including traceability and defined behavior when required trust information is missing.
Support shared semantic definitions and metadata models while preserving clear accountability within business domains.
Strengthen the team
Mentor engineers in system design, technical judgment, stakeholder engagement, and leadership.
Raise engineering standards for reliability, maintainability, testing, observability, and documentation.
Help engineers take broader ownership and communicate their recommendations effectively.
What you bring
A track record of designing, building, and operating production software or data platforms, with demonstrated impact across multiple teams.
Deep knowledge of metadata management, data governance, lineage, data quality, privacy engineering, access controls, or closely related platform domains, grounded in practical delivery.
Hands-on expertise building or extending metadata and catalog platforms such as Atlan, Alation, DataHub, OpenMetadata, or comparable systems.
A practical understanding of federated ownership models, data stewardship, semantic models, business glossaries, or certified metrics.
The ability to work across warehouse, lakehouse, streaming, and data transformation environments.
Demonstrated delivery of data contracts, automated lineage, quality checks, or policy as code.
Sound judgment in translating ambiguous business or policy requirements into clear technical designs and delivered outcomes.
Proven ability to lead initiatives across teams without direct reporting authority.
Skill in leading difficult technical or organizational conversations, resolving competing priorities, and securing clear decisions and commitments.
Strong written and verbal communication, including architecture proposals, decision documents, and presentations tailored to different audiences.
A collaborative approach grounded in listening, respectful challenge, and shared accountability.
A commitment to mentoring engineers, supported by examples of improving the effectiveness of the teams around you.
What would be valuable
Strong software engineering skills, including proficiency in a language such as Python, Java, or Go, and practical SQL experience.
Experience with distributed systems, APIs, integrations, and cloud data infrastructure, including sound judgment about reliability, consistency, security, and failure handling.
Experience implementing controls that generate operational evidence.
Delivering governed data or context services for analytics, applications, machine learning, or AI agents.
Leading platform adoption, modernization, or migration across organizational boundaries.
Representing technical work through internal forums, technical writing, communities of practice, or external presentations.
What success looks like
Partner teams understand the technical direction, the decisions required, and their responsibilities.
Cross-team discussions produce documented decisions, accountable owners, and sustained follow-through.
Priority workflows demonstrate connected governance capabilities in production, supported by clear operating ownership.
Producers and consumers can access relevant meaning, ownership, lineage, quality, and permitted-use information within their workflows.
Shared patterns reduce repeated implementation work and manual coordination.
Engineers across the group grow in technical judgment, communication, and leadership.
#LI-KS1
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role
is eligible
for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products.
This role also may be eligible for a bonus package.
Click
here
to learn more.
The estimated base pay range for this role is listed below.
$216,200
—
$324,400 USD
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Location: Bengaluru, India
We are looking for a Senior Data QE Engineer with solid experience in ETL testing and data validation, and strong SQL skills. You will design and run data quality tests, validate pipelines end to end, reconcile source and analytical data, and give engineering and business teams evidence for release decisions.
You will also automate comparisons in Python, work with Airflow pipeline runs, and use AWS and Grafana to observe pipeline health.
You will use an AI coding assistant to analyze data and author SQL, Python, and quality checks, and you will review generated output before it is used.
This position is intended for Hyderabad-based candidates who are available to work from the office.
The client runs a large application landscape and the analytical datasets behind it. Data moves from PostgreSQL sources on AWS into Snowflake through orchestrated pipelines. Quality for that data is part of delivery: test design, checks on movement and transformation, quality metrics, and practical help when data has to be corrected.
Data QE engineers own that hands-on work for data moving from source systems into analytical datasets, from test design through execution, investigation, and release-readiness reporting.
Own data quality for data moving from source systems into analytical datasets, from test design through execution, investigation, and reporting.
Design, implement, and execute data quality tests, and publish quality metrics and dashboards that producing and consuming groups can use.
Validate pipelines end to end, covering movement, transformation, completeness, history, freshness, and compliance.
Write reconciliation, drift, and quality SQL on Snowflake layered models (raw, history, silver, and gold), including slowly changing dimensions and merge behavior.
Validate PostgreSQL sources with consistent snapshot counts and checks that logical replication kept the expected data.
Use logical and physical data models and data contracts to assess downstream impact and set quality coverage.
Automate data comparison and reconciliation in Python with pytest, and keep the checks in GitHub.
Trigger pipeline runs in Airflow and read task results into the quality verdict.
Investigate quality issues and support remediation with the groups that produce and consume the data.
Design failover, outage, and volume tests and judge the evidence, including recovery time and recovery point. The platform team executes destructive and chaos tests.
Run read-only checks in pre-production and production.
Integrate quality checks with CI/CD on GitHub Actions or an equivalent tool.
Use AWS and Grafana to observe pipeline health, including CloudWatch metrics, secrets metadata, and container platform state.
Check classification, masking, and retention against the stated data rules.
Track defects to closure in Jira and keep test cases and results in TestRail.
Provide quality evidence, risks, and readiness input for releases.
Use an AI coding assistant to analyze data and author SQL, Python, and quality checks, and review generated output before it is used.
Senior-level data quality engineering experience in ETL testing and data validation.
Strong SQL and Snowflake data-modelling experience, including layered raw, history, silver, and gold models, reconciliation and drift queries, and slowly changing dimensions and merge behavior.
Experience with logical and physical data models and with assessing the downstream impact of schema and data-contract changes.
Experience validating PostgreSQL sources, including consistent snapshot counts and logical replication.
Hands-on Python automation for data comparison and reconciliation, using pytest or an equivalent framework.
Experience running and reading orchestrated pipelines in Airflow or an equivalent scheduler.
Experience validating data movement, transformation, completeness, history, freshness, and compliance from source systems into analytical datasets.
Experience diagnosing data quality issues and supporting remediation.
Experience integrating data quality checks with CI/CD using GitHub Actions or equivalent tools.
Experience with test management and defect tracking in TestRail and Jira.
Working knowledge of AWS and Grafana for pipeline observation, including CloudWatch, secrets management, and container platforms.
Experience designing resilience tests and judging evidence for failover, outage, volume, and recovery objectives.
Working knowledge of data classification, masking, and retention checks.
Experience producing data quality metrics, reports, and dashboards.
Experience with risk-based testing in Agile or Kanban teams.
Hands-on use of AI coding assistants (Cursor, GitHub Copilot, Claude Code, Codex, or equivalent) to author SQL, Python, and quality checks, with human review of generated output.
Ability to communicate clearly with engineering and business stakeholders.
Experience providing quality evidence, risks, and readiness input for releases.
Experience observing Snowflake Openflow or NiFi connector state well enough to recognize a stalled load.
Experience with custom cross-table data quality checks that publish results for dashboarding.
Familiarity with GenAI, LLMs, and agentic workflows for maintaining data quality checks.
Familiarity with RAG and MCP concepts for QE tooling and for generating test data.
Knowledge of AI-driven test optimization and coverage analytics (SeaLights or equivalent).
Experience with service virtualization using WireMock or an equivalent tool, so checks can run when a dependency is unavailable.
Experience specifying and reviewing dbt tests. Developers author those tests.
Location: United States
Workplace: Remote
ABOUT DOCKER
Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.
We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.
_______________________________________________________________________
THE ROLE
As a People Partner at Docker, you will work with managers and employees across Marketing, G&A, and Products to help teams perform, grow, and navigate everyday people needs.
This is an individual contributor role for someone with solid HR experience, clear communication, and a practical approach to solving problems. You will build trusted relationships, coach managers, and own work from start to finish. You will work independently within your scope, partnering with your manager and People Team colleagues on more complex or sensitive matters.
_______________________________________________________________________
WHAT YOU’LL DO
- Build relationships with managers and employees across your client groups. Understand their priorities, team dynamics, and how you can support them.
- Coach managers on setting expectations, giving actionable feedback, supporting development, and addressing performance concerns promptly and fairly.
- Guide managers and employees through day-to-day and moderately complex employee matters. Gather relevant facts, evaluate options, and recommend practical next steps.
- Recognize when a situation requires broader input. Raise concerns promptly and bring a clear summary, your assessment, and questions to your manager or the appropriate partner.
- Coordinate and deliver core people processes within your client groups, including performance reviews, talent reviews, compensation cycles, promotions, and engagement action planning.
- Use people data and employee feedback to identify team-level patterns, recommend actions, and track follow-through.
- Help managers clarify roles, responsibilities, and team expectations. Support defined parts of workforce planning and organizational changes in partnership with your manager.
- Work with Talent Acquisition, People Ops, Total Rewards, Finance, Legal, and other partners to resolve questions and move shared work forward.
- Support global and distributed teams, working with regional experts to account for local requirements and differences in employee experience.
- Own defined People Team projects or workstreams, managing commitments, communicating progress, and raising blockers early.
- Share knowledge and practical resources with teammates, contribute ideas for improving processes, and actively seek feedback on your own development.
_______________________________________________________________________
WHAT YOU’LL BRING
- Relevant HR experience, typically four or more years, including hands-on experience advising managers as a People Partner, HR Business Partner, or in a similar role.
- Solid working knowledge of employee relations, performance management, talent development, compensation processes, and employee engagement.
- The ability to manage moderately complex work independently, organize competing priorities, and follow through on commitments.
- Sound judgment about what you can resolve within your scope and when to involve your manager or a specialist.
- Clear, thoughtful communication. You can explain sensitive information, ask useful questions, and offer a recommendation supported by facts.
- The ability to build credibility across teams, work through disagreement respectfully, and raise concerns when something needs attention.
- Curiosity about the business and an understanding of how people decisions affect team outcomes.
- Comfort using data to identify patterns and inform practical recommendations.
- Care, discretion, and attention to detail when handling confidential information.
- Experience working with distributed or global teams, or a demonstrated ability to collaborate across locations and time zones.
- Comfort using AI tools to support your work, with independent review of their outputs and sound judgment about handling sensitive information.
- Experience supporting Marketing, Product, or G&A teams is a plus, as is experience in a technology company.
_______________________________________________________________________
WHAT SUCCESS LOOKS LIKE
In the first month, you will learn Docker’s culture, People Team practices, and the priorities and structures of your client groups. You will connect with managers, understand current people needs, and learn where to find guidance and support.
In the first three months, you will independently manage day-to-day partnering needs and assigned people processes. You will provide practical manager guidance, follow through on commitments, and bring clear assessments when an issue needs broader input.
In the first year, you will be a trusted, reliable partner to managers and employees across your client groups. You will own moderately complex work from start to finish, contribute to improvements in team effectiveness, and deliver defined projects that support People Team and business priorities.
Visa sponsorship: Not available for this role.
_______________________________________________________________________
COMPENSATION & EQUITY
All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location.
United States: $103,000 – $147,000 base
______________________________________________________________________
POSTING INFORMATION
- Open vacancy: This posting is for an existing open role.
- AI in hiring: Docker may use AI-assisted tools during our recruiting process.
- Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent.
______________________________________________________________________
PERKS & BENEFITS
- Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
- Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
- Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
- Home office support – Set up your workspace for comfort and success.
- Technology stipend – Equivalent to US$100 net per month to help support your work.
- Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
- Parental leave – 16 weeks of paid parental leave after six months of employment.
- Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
- Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
- Docker swag – Because representing the whale never gets old.
Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community.
#LI-REMOTE
Location: New York, NY (HQ); San Francisco, CA; Remote (US)
Workplace: Hybrid
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
ABOUT THE ROLE
Ramp believes that AI-powered CX organizations are the future and we are racing to build the best one in the world. Our goal is for our team to work hand in hand with AI agents to drive superlative customer outcomes and the highest-velocity AI improvement engine in the business.
This role will own the strategy and ops teams that are making that transition a reality while still delivering 24/7/365 support for our 85,000+ customers every day. You will work with the Head of CX to set the goals, measure what matters, and build the systems and programs that push the team forward. You’ll manage a small and mighty team across Business Operations, CX Analytics, Workforce Management, Learning & Development, and CX AI Operations to accomplish your goals.
We believe every CX frontline specialist has a role to play driving forward the performance of our AI agents - it is not work reserved for a dedicated AI team. Each specialist needs to be trained, coached, scheduled, and rewarded for continuous work of closing AI learning loops, ensuring AI escalations get resolved, and obsessing about how our customers are actually being served.
You'll do this while running a global support operation that has to be excellent today. Once we nail the model in CX, there will be momentum to help other operations teams adopt it.
WHAT YOU’LL DO
- Set the goals and measure what matters. Work with the Head of CX and senior CX managers to set org-wide goals, decide how we measure progress, and deliver the programs and projects that enable that strategy to flourish.
- Define how specialists and AI agents work together. Build the roles, workflows, and expectations that let specialists and AI agents serve customers as one team.
- Change what we reward. Rebuild goals, incentives, and performance management so specialists get credit for closing AI learning loops, getting AI escalations resolved, and improving how customers are actually served, alongside traditional frontline performance.
- Own global schedules, capacity, and quality. Plan coverage for 24/7/365, multi-tier, global support that holds a high bar for customers of all shapes and sizes.
- Build the training model for the new work. Both new and tenured specialists need to investigate hard issues, judge agent behavior, and contribute fixes, while still developing a deep understanding Ramp’s complex financial products. L&D should make them good at all of it.
- Turn AI progress into operating change. Know what our Investigative Copilot (specialist-facing) and AskRamp (fully agentic) can do and how well they do it. When that moves, change staffing, workflows, training, and expectations to match.
- Build and own the voice of the CX specialist to Product and Engineering. Use CX data to show technical teams where agents succeed and where they struggle, and work with them directly on tooling, prompts, and agent behavior. They own the roadmap; you make sure CX's evidence shapes it.
- Build a small, strong team. Develop and grow leaders across Business Operations, CX Analytics, Workforce Management, Learning & Development, and CX AI Operations, with clear ownership and shared goals.
WHAT WE’RE LOOKING FOR
We want an operator who has already changed how real work gets done with AI and can show the results.
- A record of strategic and operational execution inside an operating unit or fast growth business. That could be CX, Sales, supply chain, or another function where you owned the goals, the systems, and the outcomes.
- A genuine AI transformation you were on the front lines of in the last 18-24 months. You changed how a team’s work gets done and kept it running in production. You can explain what improved, what failed, and what you learned.
- Exceptional intellectual horsepower and natural curiosity, demonstrated through outstanding, standout performance across past roles in demanding environments.
- Experience leading teams and developing reports, with sound judgment about organizational design, incentives, and performance management.
- Analytical depth you use yourself: you can build or audit a capacity model, challenge a metric, diagnose an operating problem, or review an AI agent session to find the flaws.
- Credibility with Product, Engineering, and Data teams, and the ability to shape their priorities without a reporting line.
- High standards for customer quality and human accountability - you don’t compromise on the customer outcome.
HELPFUL EXPERIENCE
- Leadership spanning business operations, CX analytics, workforce management, learning and development, or AI operations or their equivalents in other operating teams.
- Experience with production AI agents, evaluations, escalation workflows, and continuous improvement.
- Taking an operating model that worked in one team and making it successful elsewhere.
HOW SUCCESS WILL BE MEASURED
- Specialists and AI agents work as one team, measured through both direct frontline performance as well as agentic velocity.
- Every specialist is trained, coached, scheduled, and rewarded for migrating successfully into an AI native version of the role.
- Learning loops close fast, AI escalations produce durable fixes, and new agent capabilities show up as operational gains.
- Customer quality goes up and 24/7/365 support stays excellent while the operating model changes.
- Other Ramp operations teams are adopting what worked in CX.
COMPENSATION
For candidates located in New York City or San Francisco, the base salary range for this role is $184,000–$250,000. For candidates located in all other locations, the base salary range will be between $175,000-$220,000.
BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL)
- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- Weekly coffee stipend
UNITED STATES
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
- One Medical annual membership
- 401(k), including employer match on contributions made while employed by Ramp
- Fertility HRA (up to $10,000 per year)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
- Pet insurance
- In-office perks: lunch, snacks, drinks, and more
- Relocation expense coverage to NYC or SF (if needed)
CANADA
- Group medical, dental, and vision coverage through Sun Life
- Life, AD&D, and disability coverage
- Fertility drug coverage (up to $4,000 lifetime)
- Group Retirement Plan with employer match (RRSP + DPSP)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay
- Employee Assistance Program and virtual care through Lumino Health
UNITED KINGDOM
- Private medical insurance through Freedom Elite
- Virtual GP and at-home care via eMed x Livi
- Workplace pension through Penfold, with salary sacrifice option
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
REFERRAL INSTRUCTIONS
If you are being referred for the role, please contact that person to apply on your behalf.
OTHER NOTICES
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice
Location: Worldwide
Launch Your Next Successful Chapter with Veta Virtual! 🚀
💸 Competitive Salary in USD | 🌍 100% Remote | 📈 Performance Incentives | 🤝 Customer Facing Leadership Role
Veta Virtual is hiring a
Customer Retention Supervisor
for one of our high growth clients in the fintech and cryptocurrency industry. This is a hands-on leadership role. You will lead a team of retention specialists, and you will also pick up the phone yourself. You will coach your team, build the playbook, and bring inactive customers back to a leading cryptocurrency kiosk platform.
🔑
Your Role
:
As a
Customer Retention Supervisor
, you will lead the retention team and drive repeat transactions, customer reactivation, and revenue growth. You will join calls yourself, so you lead by example. Your success will be measured by your team’s results and by real, trackable revenue recovered. Your day to day will involve:
Leading, coaching, and managing Customer Retention Specialists, with clear goals and accountability for results.
Making outbound calls yourself to encourage repeat transactions and reactivate inactive customers.
Building and updating SOPs, calling workflows, scripts, and training materials.
Managing daily outreach, agent schedules, and campaign assignments.
Running retention campaigns, including promotions, discount incentives, and abandoned transaction follow-ups.
Tracking team KPIs, such as calls, conversion rates, repeat transactions, reactivation rates, and revenue.
Holding regular call reviews and coaching sessions to help every agent improve.
Studying customer activity and campaign results to find new retention opportunities.
Keeping accurate CRM records, agent scorecards, and regular performance reports.
Handling escalated customer concerns and working with Marketing, Support, Sales, Operations, and Compliance.
Supporting the hiring, onboarding, and training of new team members.
✅
What You’ll Need
:
At least 3 years of supervisory or leadership experience in customer retention, outbound sales, or contact center operations.
Proven success in customer conversion, retention, and reactivation, while leading a performance-driven team.
Experience building SOPs, call scripts, and training materials.
Strong coaching, objection-handling, and communication skills.
Strong analytical skills, with the ability to turn performance data into clear action plans.
Ability to balance hands-on customer work with team management in a fast-paced, entrepreneurial environment.
Proficiency in Microsoft Office, especially Excel, and experience with CRM and outbound calling platforms.
Comfort using AI tools to support research, scripting, and daily productivity is a strong plus.
Bonus: experience in fintech, financial services, cryptocurrency, or a regulated environment.
Bonus: basic knowledge of cryptocurrency and blockchain, and genuine passion for fintech.
💼
What We Offer
:
💸 Competitive salary in USD, paid consistently every month, no matter where you are.
📈 Performance based incentives, so your results and your team’s results are recognized and rewarded directly.
🌴 10 paid vacation days per year plus all U.S. federal holidays.
💻 100% remote, work from anywhere in LATAM or Europe with a professional home setup.
🚀 A fast paced, high growth environment at the forefront of the global fintech and cryptocurrency industry, where your leadership directly drives company revenue.
🤝 A collaborative, high trust culture through Veta Virtual and our client, where your growth is taken seriously from day one.
Ready to Apply?
If you are ready to lead a team, pick up the phone, and build a retention engine that wins customers back, apply now and launch your next chapter with Veta Virtual.
Once you apply, you will be invited to complete two short two minute video questions as part of our screening process. It is your first opportunity to show us your leadership style, your energy, and what makes you the right person for this role. We can’t wait to meet you!
Location: Canada
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is 299,300 to 372,600 CAD plus a target annual bonus of 20 percent of base. That's total target cash of roughly 359,160 to 447,120 CAD. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Location: United States
What The Role Is
We're hiring a Staff MLE for the Discovery team to own recommendations and personalization across Babylist's consumer experience — the homepage feed, product recs, search, and the ML-powered systems that make registry building feel effortless.
Babylist was built on editorial recommendations: products chosen by people with deep baby gear expertise. That editorial foundation is a big part of why millions of families trust us. We're now building ML-powered personalization on top of it, using one of the richest first-party datasets in parenting.
We're early in this work, and we have a real mandate. A small Discovery team has initial retrieval and reranking models live on parts of the site and a steady cadence of A/B tests. We are looking for a Staff MLE who has seen personalization done well at scale and can set the technical direction for where we go next.
Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting personalization problems in consumer e-commerce: latent intent, life-stage progression, multi-stakeholder gift dynamics, deep declarative signal in millions of completed registries, cross-retailer datapoints, and a user who genuinely wants help.
If you want to join a mature ML org and tune models at the margins, this isn't the right role. If you've worked inside a strong recommendations team, learned what good looks like, and want to build from zero-to-one at a company earlier in the journey, read on.
What You'll Own
You'll be the technical lead for personalization on the Discovery team, working alongside a PM, Engineering Manager, Senior MLE and fullstack software engineers. You set where our models go over the next year or two, sequence the bets that get there, and stay deep in building. A few examples of the problems you’ll get to shape:
Product recommendations across every surface.
Product detail pages, add-next recommendations after someone adds to their registry, vibes/aesthetic representations of products and the shared models underneath them.
Personalizing the Feed.
Deciding which products, editorial content and social content each family sees, and in what order.
Personalizing search.
Bringing what we know about a family into search results, and helping decide how much search should share retrieval and ranking with recommendations.
Making Addie (our AI registry assistant) better at recs.
Working with the team behind Addie so its product suggestions draw on the same models and signals as the rest of the site.
In practice, you will:
Take a fuzzy business problem from first sketch to production model, and own whether it moved the metric.
Make the modeling and architecture calls that span surfaces and are expensive to reverse.
Design the evaluation, offline and online, that tells us a model is good before and after it ships.
Know when a rule or a simple baseline is the right first step, and when it's time to pursue more advanced approaches.
Partner with product, design and data to help shape what's worth building.
Coach engineers on the team, and more broadly be an ML expert and resource to the wider engineering org.
Who You Are
You’ve shipped recommendation and/or personalization systems that reached real users at scale within a consumer product, and can point to the business impact of your work. You’ve done this within a team that did ML well — you know what good looks like, and are motivated to bring that to a company earlier in their ML journey.
You bring:
Expertise in recommender fundamentals: for example, candidate generation vs. ranking, offline vs. online evaluation, cold start solutions, and handling position and popularity bias.
Fluency in the Python ML stack and comfort owning models through deployment and monitoring, including contributions to our application backend.
An ability to take an ambiguous problem and start moving before anyone hands you the full picture.
A builder's instinct for early-stage ML. You understand effort vs. effectiveness tradeoffs and can advocate for when a rule beats a model, or a model is “good enough” for early learnings.
An outcome and user focused mindset. You measure yourself by business impact, and you can connect a model change to user experience & registry adds, conversion or revenue.
AI-native daily practice. You're already using AI to move faster and improve your output, and you stay curious about what's coming next.
Compensation
We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
Location: North America
Workplace: Remote
At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires.
Founded in 2019, Linear has become the platform of choice for more than 50,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship.
Over the past years, Linear has experienced incredible organic growth and has become an instrumental tool for many of the world’s best product teams. We believe customer support should always feel like an extension of that experience. As a Product Support Specialist at Linear, you’ll contribute to the future of our product by surfacing customer feedback and insights, contributing to our technical documentation, and engaging a technical customer community via social channels.
Location & work mode
Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based within U.S. and Canada Eastern or Central Time. You can work from anywhere within those time zones. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel.
What you’ll do
- Support customers in end-to-end engagement, including onboarding, account setup, debugging issues, feature and integration discovery
- Investigate and resolve inbound customer issues reported through all communication channels, including email, Slack, Twitter, and Reddit
- Partner with our engineering team to document and reproduce bugs
- Surface trends and insights from customer feedback to the team at large to inform product choices
- Lead select strategic projects to improve the support experience, internal knowledge sharing, and product operations
What we're looking for
- Passion about technology, quality, and Linear’s mission
- Excellent communication and customer service skills and experience working with a technical or engineering user base. Ability to adapt your communication approach to non-technical users.
- Experience troubleshooting technical issues, including APIs and integration setups. Ability to reproduce bugs with Linear and our integrations in various environments (different browsers, Windows, Mac, Mobile).
- Familiarity with SQL, Javascript, APIs, and GitHub is a plus. If you don’t have direct experience in these areas, curiosity to learn more is desirable as well. Please note that this is not a product engineering role.
- Based in U.S. or Canada Eastern or Central Time only.
What we offer
We're a small, focused team that cares deeply about the quality of our work and the people we do it with. Here's what you can expect:
- Competitive salary and equity
- Employee-friendly equity terms including early exercise in the US and extended exercise windows
- Daily meal and coffee stipend on every workday
- Paid co-working space or desk
- Health coverage (based on country requirements)
- 5 weeks paid vacation, plus local statutory holidays
- 4 months paid parental leave
- Paid month off after 4 years & every 2 years thereafter
- Regular team events and off-sites
- Remote-first with no required commute
Compensation
For US-based candidates, the expected cash compensation range for this role is $95,000—$135,000. For sales roles, this range represents on-target earnings (OTE), including base salary and variable compensation; for all other roles, it represents base salary. Final compensation is determined based on job-related knowledge, skills, and experience. For sales roles, actual earnings vary based on sales performance. Equity is a meaningful part of all offers at Linear.
Learn how we think and work
- A story about our mission: Read Me https://linear.app/readme
- Building our teams: Why and how we do work trials at Linear https://linear.app/blog/why-and-how-we-do-work-trials-at-linear
- How we work: Designing remote work at Linear https://linear.app/now/designing-remote-work-at-linear
- How Linear uses Linear: How our Customer Experience team works in Linear https://linear.app/now/cx-in-linear
- A video series: Conversations on Quality https://linear.app/quality
- Our recent tender offer: Sharing Linear’s growth with the people building it https://linear.app/now/sharing-growth-with-the-people-building-linear
A note on recruitment fraud: all official Linear hiring communication comes from an @linear.app http://linear.app email address, and all open roles are listed at linear.app/careers http://linear.app/careers. We never ask candidates for payment or financial information. Suspicious messages can be reported to security@linear.app.
Linear is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.
Location: San Francisco
Workplace: Remote
Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.
ABOUT THE COMPANY
Our client is a Series B enterprise AI startup that raised $108M from a16z, Benchmark, First Round, BoxGroup, and YC, building infrastructure that turns complex documents into structured, AI-ready data. Its API-based platform processes PDFs, images, spreadsheets, and other unstructured files, helping organizations build production AI applications and automate document-intensive workflows.
Our client supports AI-native startups and large enterprises with demanding accuracy and deployment requirements. The team is founder-led and engineering-first, with engineers working directly with customers and using what they learn to improve the product.
THE MISSION
Make complex document data reliable enough to build on.
Our client helps organizations unlock information inside unstructured files while preserving the detail and structure that downstream applications depend on. The goal is to deliver accurate, usable data that holds up in production, not simply extract text that looks convincing in a demo.
THE OPPORTUNITY
Own the technical work that turns an enterprise evaluation into a successful production deployment.
As a Forward Deployed Engineer, you’ll build applications, run evaluations, troubleshoot integrations, and stay close to customer results. You’ll partner with sales during technical evaluations, then own technical success for 1-3 enterprise accounts, helping customers resolve issues, deepen adoption, and expand into additional use cases.
This is a founding role within our client’s developing FDE function. You’ll work directly with founders, product, and engineering to shape the platform and establish how future deployments are delivered.
The role combines substantial engineering work with customer relationships and deployment responsibility. Both backend-leaning engineers and customer-facing FDEs are welcome, but independent coding and production deployment ownership are essential. This position requires full-time, in-person work in San Francisco, five days per week.
WHAT YOU'LL DO
- Turn customer requirements into working applications and integrations
- Partner with AEs and SEs on evaluations, custom demos, and competitive benchmarking
- Build custom applications, agents, evaluation tools, and product enhancements
- Own technical success for 1-3 enterprise accounts, meeting weekly or biweekly
- Resolve deployment and integration issues to deepen adoption
- Build diagnostics, dashboards, and evaluation harnesses to measure performance and catch regressions
- Explain technical decisions and trade-offs to customer stakeholders
- Identify new use cases and expand deployments across teams
- Translate customer insights into product improvements and engineering priorities
WHAT YOU BRING
- 3+ years of full-time production engineering experience shipping software for enterprise customers
- Experience at a recognizable, high-growth startup with strong engineering standards
- Independent ownership of building, deploying, and supporting production applications or AI pipelines
- Strong production-level Python and engineering fundamentals
- Solid understanding of AI, LLMs, and machine learning concepts
- Use of Claude, Codex, or similar coding tools beyond autocomplete, guided by sound technical judgment
- Enterprise deployment experience spanning integrations, troubleshooting, and customer-specific constraints
- Clear communication and confidence leading technical customer conversations
- A quantitative approach to debugging, experimentation, and performance measurement
- Willingness to work on-site in San Francisco five days per week
KEY SUCCESS DRIVERS
- Ownership: You identify what needs doing and follow through until the issue is resolved and the deployment works
- Technical judgment: You build solutions that fit the problem and validate them with evidence
- Customer judgment: You understand the customer’s technical context and connect engineering work to useful outcomes
- Quality: You move quickly without overlooking the details that determine production reliability
- Communication: You explain trade-offs clearly and keep technical and business stakeholders aligned
- Resourcefulness: You build the tools, diagnostics, or prototypes needed to unblock progress
- Adaptability: You move comfortably between coding, evaluations, troubleshooting, and customer conversations
WHY JOIN?
- Compensation: 220,000-320,000 annual salary, plus competitive equity
- Scope: Help build the FDE function while owning evaluations, implementation, and ongoing technical outcomes
- Production impact: Solve document-processing and deployment challenges that directly affect enterprise AI applications
- Product influence: Work directly with founders and engineering to turn customer needs into platform improvements
- Team: Join a founder-led, engineering-first environment with close collaboration across product, sales, and customer success
- Benefits: Medical, dental, and vision insurance; unlimited PTO; flexible parental leave; and up to $150/month in eligible health and wellness reimbursement
- Office support: Free daily lunch and reimbursed transportation
- Visa support: Open to visa transfers (e.g. OPT, H1B transfers) and sponsorship
INTERVIEWING PROCESS
1. HR screening
2. Hiring manager screen and technical interview - 30 minutes: Live Python coding to assess engineering fundamentals and problem-solving.
3. On-site practical assessment: Build an application relevant to the role, with a focus on engineering depth or technical presentation and customer communication.
4. Offer extended.
We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.
Location: Remote (Central & South America)
Workplace: Remote
ABOUT CLIPBOARD
Our mission is to uplift as many communities as possible. We do this through our app-based marketplace that connects healthcare professionals with the workplaces that need amazing workers. This enables hundreds of thousands of people to achieve financial stability for themselves and their families while providing essential care to millions of people across the U.S.
Founded in 2016, we are a remote-first team of over 1,000 people building a top Y-Combinator company https://www.ycombinator.com/topcompanies/ and have been profitable since 2022. We’re the leader in Long-Term Care staffing and are rapidly expanding into Home Health, Hospitals, and more, meaning we have more work to do than people to do it, and are growing our team to support millions more people and their communities.
ABOUT THE ROLE
Working with Workplace customers (B2B) means being at the front line in our efforts to support healthcare facilities in delivering better care. The Workplace team is unified by our common goal: to represent our obsession with the customer experience through thoughtful action.
Clipboard is looking for highly motivated, customer-focused individuals to join our team as B2B Client Support Specialists (Workplace Support Agents).
This role is open to candidates of all experience levels—what matters most is your ability to handle business customers professionally and solve problems effectively. No specific degree required.
SUCCESS FACTORS
- Customer-Centric Mindset – You genuinely care about helping customers and take ownership of their problems.
- Strong Communication Skills – Clear, professional English (both spoken and written) is critical for success in this role.
- Proactive Problem-Solving – You don’t just follow scripts—you think critically and find long-term solutions for customers.
- High Accountability – We value people who hold themselves to high standards and consistently deliver results.
Responsibilities
- You will engage with our Workplace customers over both voice and email correspondence.
- Deliver fast, accurate, and empathetic support to our workplace customers across voice and email, resolving shift, payment, and platform-related issues in real time
- Navigate tools like Zendesk and the Clipboard portal to investigate cases, update form fields, log clear internal notes, and maintain accurate documentation
- Apply sound judgment and critical thinking to troubleshoot issues, follow or adapt workflows, and escalate only when necessary
- Develop deep expertise in our products and processes to identify recurring issues or process gaps, helping improve both customer experiences and internal operations.
- Work cross-functionally with teams such as Billing, Account Management, and Worker Operations to gather the necessary information and ensure customer issues are resolved effectively
- Uphold our values https://www.clipboardhealth.com/careers such as unreasonably fast, ownership, and uncomfortably high standards in every interaction
Why Join Clipboard?
- 100% Remote – Always. Work from anywhere in the world.
- Fast-Paced Startup Environment. Join a company that values curiosity, independence, and growth.
- A Hiring Process That Rewards Skills, Not Just Experience. Every applicant gets a fair shot—our selection is based on real-world problem-solving ability, not just credentials.
- Opportunity to make a significant impact with our workplace customers
Hiring Process
1. Application
2. Case Study
3. Interview with Hiring Manager
4. Executive Interview
5. Offer
Quick Note on Scammers:
Clipboard would never ask you for money or your bank details to participate in our hiring process. Report any scammers impersonating the Clipboard hiring team members here https://forms.gle/SyGaxHFbon7Hg9fW6.
Location: Remote: United States
Workplace: Remote
At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure.
Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users.
Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development.
We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you.
APPLYING TO RENDER
We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team.
We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed.
Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time.
ABOUT THE ROLE
DX Engineering shows developers what building on Render is actually like. We make the tutorials, demo apps, templates, and videos that get developers to try Render, and we build the agent skills and internal tooling that keep that work running at scale. We're also often the first real users of what Render ships. We test major releases end to end, the way a customer would, and tell Product and Engineering where they fall down before customers hit it.
As a DX Engineer, you'll own technical content and code from the first idea to a working sample app, docs, and video. You'll work with DevRel, Product Marketing, Product, and Engineering, and you'll have real influence over how developers and coding agents discover and adopt Render.
This is a remote role within the US, with the option to work out of our headquarters in San Francisco.
WHAT YOU'LL DO
- Build tutorials, demo apps, and videos that show developers how to build real things on Render, with a focus on AI applications, agents, and Render's AI runtime products like Render Workflows.
- Own Render templates and the render-examples GitHub org for the frameworks developers ask about most. Everything you ship has to deploy and run.
- Build agent skills, automation, and internal tools so the team stops doing repetitive content and ops work by hand.
- Improve how Render shows up in LLM and answer-engine results. Dig into why Render is missing from an answer it should be in, then ship the content or fix that changes it.
- Alpha test new releases end to end and write up what breaks, with enough detail for Product and Engineering to act on.
- Contribute code to developer-facing surfaces like the Render CLI, MCP server, SDKs, and docs.
- Shape the content roadmap and quality bar with Product, Engineering, and Marketing, and iterate on feedback and metrics.
- Set technical direction for DX Engineering's content and tooling, and raise the bar for the rest of the team through reviews, standards, and your own work.
WHAT WE'RE LOOKING FOR
- 8+ years building developer content, or working as an engineer who teaches, at a developer tools or infrastructure company.
- Experience setting technical direction and raising the bar for a team.
- Full-stack engineering experience. Strong backend skills (Node.js/TypeScript, Python, Postgres), comfort with Docker and containers, and enough frontend skill to ship sample apps end to end.
- Deep, hands-on knowledge of AI agents and the workloads they run. You've built and deployed agents that call tools, run code in sandboxes, and handle long-running tasks with retries and state, and you know what infrastructure each of those needs.
- Experience with the agent stack: MCP servers, agent frameworks, LLM APIs, evals, and durable workflow or background job systems.
- Daily fluency with coding agents like Claude Code, Codex, and Cursor, and the taste to ship quality work at a steady cadence with them.
- Excellent technical writing. You know what world-class developer content looks like.
- A track record of owning projects end to end with little direction.
- Strong intuition for developer tools and a love of well-crafted user experiences.
NICE-TO-HAVES
- You've used Render before, professionally or on side projects.
- Experience with AEO or SEO, or with measuring how content performs in LLM answers.
- A public body of work: talks, a YouTube channel, popular open source repos, or a well-read blog.
- Experience presenting workshops and technical talks.
SOME PROJECTS YOU MIGHT WORK ON
- A video series on building and deploying an MCP server on Render.
- A sample app for an upcoming launch, built with Product and Engineering ahead of release.
- An agent skill that turns a tutorial into a tested, deployable template.
- Tracing why coding agents fail on a specific docs page, then shipping the fix.
If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need.
BENEFITS
- 4 weeks of paid vacation.
- 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return.
- Long-term disability, life insurance, and 401K plans.
- 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well.
- Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc.
- Monthly cell phone and internet subsidy.
- Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders.
- Continuous learning benefits & related support.
This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization.
Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
We encourage all who are interested to apply. We can't wait to hear from you!
Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view
Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view
Location: London
Workplace: OnSite
ABOUT US
At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale.
We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry.
More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale.
ABOUT THE ROLE
We're hiring a Vice President to own and lead our EMEA business. You'll inherit a team of 20+ quota-carrying Commercial and Enterprise AE's across four hubs: London, Amsterdam, Munich, Stockholm and be responsible for building the management layer, operating model and partner ecosystem that takes the EMEA region from early traction to consistent, scaled revenue.
This is a second-line leader role that will see you report directly to the Global Vice President of Sales and operate with meaningful autonomy across pipeline, hiring, partner relationships and executive engagement.
WHAT YOU'LL OWN
Team leadership and performance
- Lead, develop and expand the Sales teams across EMEA from day one
- Run weekly pipeline reviews, deal coaching sessions, and forecast calls with precision and consistency
- Identify and close performance gaps early: coach the team to close larger deals faster and navigate complex, multi-stakeholder cycles
- Build a culture of accountability and development; create clear career paths for senior individual contributors, including first-line management opportunities as the team scales
Revenue
- Own the EMEA number: quarterly and annual quota attainment across all sub-regions
- Build and maintain a healthy pipeline that supports consistent delivery and predictable forecasting to leadership
- Engage directly in strategic deals as executive sponsor, bringing credibility and commercial weight to enterprise negotiations
- Establish the region's strongest lighthouse accounts across key industry verticals, building referenceable wins that anchor LangChain's market position in EMEA
Hiring
- Manage multiple open roles across EMEA simultaneously: owning the full hiring lifecycle across pipeline, assessment and closing
- Partner with the internal talent team to move at pace without compromising on quality
- Define the headcount profile for EMEA beyond Q4 and feed into H1 planning, ensuring the team is built ahead of the revenue curve
Partner ecosystem
- Owns hyperscaler and GSI/RSI relationships (AWS, Google Cloud, Azure, and key SIs) across EMEA
- Develop a structured partner motion that generates qualified pipeline and supports deal acceleration, reduces risk and drives expansion
- Represent LangChain at partner QBRs and executive engagements in region
Market presence
- Represent LangChain as a keynote-ready leader at partner events, customer engagements, and industry conferences across the region: including KubeCon, Money20/20, Nordic AI summits, and customer EBCs
- Build LangChain's brand with technical buyers, CIOs, and innovation leaders across Northern Europe's most important enterprise accounts
- Bring intelligence on the EMEA markets back to the Global VP of Sales and product teams to inform roadmap and go-to-market positioning
WHAT WE'RE LOOKING FOR
Experience
- 10+ years in enterprise SaaS sales, with at least 5+ years in a regional or sub-regional leadership role managing quota-carrying AE's
- Demonstrable track record of hitting and exceeding regional revenue targets across multiple quarters
- Experience managing teams across multiple countries and time zones, with the cultural intelligence to operate across EMEA
- Background selling to technical buyers (engineering leaders, CTOs, platform teams): you understand how developer tools get evaluated and adopted
- Experience in the AI, data, or developer tooling space strongly preferred; familiarity with the LangChain ecosystem is a meaningful plus
Leadership
- You've run teams of 20+ AEs before and know the difference between managing and coaching
- You can hold a forecast conversation with a VP and a deal coaching session with an AE in the same afternoon and add value in both
- You hire well and fast. You know what good looks like for enterprise AE profiles and you can run structured hiring processes across four open roles simultaneously
- You've built or contributed to a partner motion before: you understand what "partner pipeline" means in practice, not just in theory
Operating style
- You bias toward action. You don't wait for a playbook to be handed to you: you build it
- You're comfortable with ambiguity and early-stage scale. This is not a role with a fully defined motion; you'll shape a significant part of it
- You communicate clearly and directly, to your team and to leadership
- You're present in the market. You attend the right events, know the right people and build relationships that translate into pipeline and retention
COMPENSATION PHILOSOPHY:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
ГибридNew York
Canada
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УдалённоUnited States; Experience working with distributed or global teams, or a demonstrated ability to collaborate across locations and time zones
ГибридseniorNew York, NY (HQ); San Francisco, CA; Remote (US); Relocation expense coverage to NYC or SF (if needed)
УдалённоМожно работать из любой страны
Canada
United States
УдалённоСША; This role is open to candidates based within U.S; You can work from anywhere within those time zones
United States - Remote
УдалённоSan Francisco
УдалённоThis role is open to candidates of all experience levels—what matters most is your ability to handle business customers professionally and solve problems effectively
УдалённоRemote: United States
ОфисLondon; Experience managing teams across multiple countries and time zones, with the cultural intelligence to operate across EMEA