Location: Lanham, MD
Overview:
The nursing graduate shall practice only under the direct supervision of a registered nurse who is physically present on the unit to (1) cosign medication transcription, medication administration, and nursing documentation; and (2) continually observe, assist, coordinate, evaluate, and monitor the nursing graduate. The nursing graduate shall use the initials NG after the nursing graduates name as credentials.
Transcribe medication orders per written policies and procedures once skill validation has been successfully completed.
Administer medications and controlled substances and sign controlled substances sheets
Document in the medical record with the abbreviation NG
Perform patient assessments after the initial assessment or after the first assessment of the shift performed by the registered nurse.
Perform and document routine procedures taught within the nursing graduates generic nursing program including placing nasal gastric tubes, performing urinary catheterizations, applying sterile dressings, performing blood sugar checks and obtaining specimens.
Graduate of an accredited registered nursing program.
Graduate of an accredited registered nursing program. Eligible to sit for NCLEX – A nursing graduate shall cease practice as a nursing graduate immediately if the nursing graduate fails two attempts at the NCLEX exam or has not successfully taken and passed the NCLEX exam within 120 days of application to the board of nursing.
A nursing graduate shall cease practice as a nursing graduate:
(a) No later than 120 days after the date the nursing graduate submitted an application to the Board; or
(b) Immediately if the nursing graduate fails the second NCLEX examination.
A nursing graduate may not:
(a) Work without the physical presence of and direct supervision by a registered nurse;
(b) Refer to oneself or practice as a registered nurse (RN) or licensed practical nurse (LPN);
(c) Be considered a staff person for purposes of a staffing pattern;
(d) Accept charge responsibilities; or
(e) Perform initial patient assessment or the first patient assessment of a shift, develop patient plans of care, evaluate or document patient discharge, or independently administer medications or intravenous therapy.
Luminis Health Benefits Overview:
Medical, Dental, and Vision Insurance.
Retirement Plan w/employer contribution.
Paid Time Off.
Employee Tuition Assistance Benefits.
Employee Referral Bonus Program
Employer Paid Holidays, Disability, and Life/AD&D for full time employees
Wellness Programs/Employee Assistance Programs and more
Pay Range
$29
—
$36 USD
Luminis Health Benefits Overview:
• Medical, Dental, and Vision Insurance
• Retirement Plan (with employer match for employees who work more than 1000 hours in a calendar year)
• Paid Time Off
• Tuition Assistance Benefits
• Employee Referral Bonus Program
• Paid Holidays, Disability, and Life/AD&D for full-time employees
• Wellness Programs
• Employee Assistance Programs and more
*Benefit offerings based on employment status
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To enable this feature, select "yes" when asked to "opt-in to receive text messages" and to "Receive updates from a recruiter about this job via SMS" when completing your application. Once you are opted in, you can easily opt-out at any time.
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Location: United States of America
What We Do:
Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact.
Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection.
Huntress now secures more than 6M endpoints and 17M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other.
Reports to: Senior Manager, Community - Field
Location: Remote US
Compensation Range: $94,400 to $118,000 base plus bonus and equity
What You'll Do:
You are the person who brings Huntress to life in the room. You travel to roadshows, tradeshows, and other events, meet people who didn't plan to meet you, and turn genuine conversations into momentum for the business. Give More Than We Take shows up in the way you create value first, listen closely, and build relationships that feel human rather than transactional.
You are Outcome-Obsessed about creating meaningful engagements at events from the moment you leave your house to the moment you return, knowing that booth hours are just the tip of the iceberg. You make sure the right prospects receive thoughtful follow-up, account executives get the context they need, and qualified conversations become fully booked demo opportunities. You take ownership of the details, spot what is missing, and use sound judgment when the process needs to bend to serve the customer and the team.
Responsibilities:
Travel to assigned roadshows, tradeshows, and other events up to 60% of the time
while representing Huntress with energy, professionalism, and a clear understanding of the audience.
Drive meaningful traffic to the Huntress booth with pre-event outreach, and by starting conversations, engaging attendees, and creating reasons for the right people to stop and learn more.
Execute on-site activations and feet-on-the-street account-based marketing activities as directed by your manager.
Build genuine relationships with prospects and partners, in transit, in hallways, over drinks, over dinner, at the booth, at event receptions and parties. Wherever the MSPs are, that’s where you’ll be found.
Drive interest through thoughtful conversation, and book demos at in-person events.
Manage event follow-up and relationship progression so account executives receive timely context, clear next steps, and strong opportunities to pursue.
Use AI tools to research target accounts, prepare for conversations, organize event notes, and draft timely follow-up while applying sound judgment to the final work.
What You Bring to the Team:
Experience engaging prospects at tradeshows, roadshows, conferences, or other in-person events is valuable.
You are curious, self-starting, eager to learn, driven, and comfortable taking initiative without waiting for perfect instructions.
You can engage strangers naturally, make small talk that leads somewhere useful, and build relationships without making the interaction feel transactional.
You are travel-ready and comfortable working in environments that require frequent movement, quick judgment, and consistent energy.
You are detail-oriented and able to follow a process while recognizing when the situation calls for a thoughtful deviation.
You use AI to work faster and smarter in day-to-day preparation, research, and follow-up, with good judgment about accuracy, privacy, and when human context matters most.
What We Offer:
100% remote work environment - since our founding in 2015
Generous paid time off policy, including vacation, sick time, and paid holidays
12 weeks of paid parental leave
Highly competitive and comprehensive medical, dental, and vision benefits plans
401(k) with a 5% contribution regardless of employee contribution
Life and Disability insurance plans
Stock options for
all
full-time employees
One-time $500 reimbursement for building/upgrading home office
Annual allowance for education and professional development assistance
$75 USD/month digital reimbursement
Access to the BetterUp platform for coaching, personal, and professional growth
Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are.
We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status.
We do discriminate against hackers who try to exploit small businesses.
Accommodations:
If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to
accommodations@huntresslabs.com
. Please note that non-accommodation requests to this inbox will not receive a response.
Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our
Candidate Privacy Notice
for more details on our practices and your data privacy rights.
Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are.
We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status.
We do discriminate against hackers who try to exploit businesses of all sizes.
Accommodations:
If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to
accommodations@huntresslabs.com
. Please note that non-accommodation requests to this inbox will not receive a response.
Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our
Candidate Privacy Notice
for more details on our practices and your data privacy rights.
#BI-Remote
Location: United States
Workplace: Remote
Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality.
We’re looking for a Legal Counsel, Employment to help us support a growing global team the Webflow way: moving quickly, working collaboratively, and staying thoughtful about risk. You’re a bright, pragmatic, self-motivated employment attorney with 4+ years of counseling and litigation experience at a law firm and/or in-house. You’ll use that background to give timely, practical, business-minded advice, primarily to our Employee Relations and People teams around the world, so they can do their best work without unnecessary barriers. You have experience litigating and/or counseling on compliance with federal and state anti-discrimination, harassment, and retaliation laws, ideally including analysis under California law. Prior in-house or seconded experience at a technology company is a plus, but not required. You’re an entrepreneurial, resourceful self-starter who thrives in a fast-paced, dynamic environment, builds strong relationships, and is curious about supporting a global workforce.
ABOUT THE ROLE:
- Location: Remote-first (United States)
- Full-time
- Permanent
- Exempt
- The cash compensation for this role is tailored to align with the cost of labor in different geographic markets. We've structured the base pay ranges for this role into zones for our geographic markets, and the specific base pay within the range will be determined by the candidate’s geographic location, job-related experience, knowledge, qualifications, and skills.
- United States (all figures cited below are in USD and pertain to workers in the United States)
- Zone A: $158,000 - $190,000
- Zone B: $148,000 - $178,000
- Zone C: $140,000 - $168,000
This role is also eligible to participate in Webflow's company-wide bonus program. Target amounts are a percentage of base salary and vary by career level. Payouts are based on company performance against established financial and operational goals.
Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
- Application Information:
- Application deadline: applications accepted on an ongoing basis until position is closed and filled
- This posting is for an existing vacancy
- Reporting to the Associate General Counsel, Corporate
As Legal Counsel, Employment, you’ll:
- Give practical, day-to-day employment advice on a wide range of issues, including HR practices, performance management, terminations, leaves of absence, investigations, and accommodations. Help the business move fast while staying clear-eyed about legal risk.
- Investigate and manage pre-litigation and litigation matters. Build and carry out strategies for early resolution where it makes sense, and partner with outside counsel when needed.
- Interpret and advise on policies and procedures using your knowledge of state, federal, and international employment laws (e.g., FMLA, ADA, FLSA, NLRA, Title VII, and their state and international equivalents). Turn them into guidance people can actually use.
- Support a global workforce with legal counsel that works across borders, cultures, and time zones.
- Partner closely with Webflow’s Employee Relations and People teams on employee complaints, investigations, performance management, and accommodations.
- Collaborate with the Employment Legal and People teams to build strong, scalable processes that keep us compliant with applicable state, federal, and local laws.
- Track developments in employment law across U.S. jurisdictions and internationally, and spot emerging trends early so Webflow can get ahead of them.
ABOUT YOU:
Requirements:
- 4+ years of employment law experience at a leading law firm and/or in-house, with an interest in advice and counseling
- Global workforce experience is a plus, not a requirement. If you’ve supported teams across borders in-house, you’ll have a head start with a company that works across time zones and jurisdictions.
- Non-negotiable requirements
- Active member in good standing of a State Bar, and eligible to practice in the jurisdiction where you’re based.
- J.D. from a top-tier law school.
You’ll thrive as Legal Counsel, Employment if you:
- Are a sharp problem-solver with sound judgment and excellent written, verbal, and interpersonal communication. You can make complex legal topics clear and useful for the business.
- Think creatively and strategically on your feet. You stay steady under pressure, juggle complex workloads and shifting priorities across many stakeholders, and help teams move quickly with confidence while staying thoughtful about risk.
- Are a resourceful self-starter who is driven by results, finds a path where others see a barrier, and works with Webflow’s collaborative, innovative spirit. You hold yourself to high standards and strong ethics.
- Build trust with cross-functional partners across the Legal Department and the company, and be the kind of counsel teams want to bring in early.
- Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact.
OUR CORE BEHAVIORS
- Build lasting customer trust. We build trust by taking action that puts customer trust first.
- Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act.
- Reinvent ourselves. We don't just improve what exists, we imagine what's possible.
- Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.
BENEFITS
- Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company.
- Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums.
- Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions.
- Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired.
- Wellness for the whole you. Access to mental health resources, therapy and coaching.
- Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally.
- Stipends to support our distributed team. Localized support for cell, Wi-Fi, and WFH expenses to help you settle into your best remote life.
- Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.
Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.
BE YOU, WITH US
At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.
STAY CONNECTED
Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.
PLEASE NOTE:
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. Upon interview scheduling, instructions for accommodation requests will be administered.
To join Webflow, you'll need a valid right to work authorization depending on the country of employment.
If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes.
Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-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.
Senior Director, Strategic Development
Position Overview
Sony Interactive Entertainment is entering an important new chapter in its evolution looking to expand business and identify future growth opportunities. This is a senior leadership position for an individual who combines exceptional strategic judgment with the ability to activate change across complex, highly accomplished organizations. The successful candidate will help SIE move beyond strategy as an annual planning exercise toward a continuous discipline of strategic choices, organizational alignment, experimentation, and measurable business outcomes.
Working directly within the Business Strategy team alongside senior leaders across PlayStation, this individual will build the frameworks, decision mechanisms, and leadership practices that enable executives to own the outcomes of the company's strategic evolution.
The central purpose of this role is not simply to develop strategy. It is to help the organization become better at continuously making, activating, and adapting strategic decisions.
Key Responsibilities
Activate PlayStation's Strategic Transformation
Translate PlayStation's long-range strategic direction into clear, actionable enterprise priorities that connect the company's existing strengths with future growth opportunities.
Help operationalize the strategic shifts defining PlayStation's evolution, including developing new value propositions, driving business model adaptation to new customers and opportunities and moving from periodic planning to continuous strategic adaptation.
Establish practical frameworks that clarify what SIE must preserve, evolve, and newly develop over the next three to five years.
Partner with functional executives to translate enterprise strategy into meaningful choices, commitments, and measurable outcomes within their organizations.
Identify structural, cultural, and operational barriers to transformation and help leadership teams address them.
Activate the strategy by embedding it within cross functional leaders to own it and adapt it as assumptions change.
Establish Continuous Strategic Planning and Adaptation
Build a strategy capability that operates throughout the year, responding to market shifts, emerging technologies, competitive developments, and organizational learning.
Design and implement a continuous strategy operating rhythm, connecting three-to-five-year ambitions with annual priorities, quarterly strategic reviews, and ongoing opportunity assessment.
Develop scenario-planning, strategic sensing, and portfolio-evaluation frameworks that allow leadership to anticipate change rather than simply respond to it.
Connect insights from product, commercial, finance, technology, studios, and external partners into an evolving view of PlayStation's future.
Create the right level of materials for decision-oriented executive forums and then orchestrate those important meetings to find emerging opportunities, challenge assumptions, and recommend adjustments to strategic priorities.
Build mechanisms for leaders to revisit investment assumptions and reallocate attention and resources as evidence changes.
Influence and Mobilize Cross-Functional Executive Leadership
Serve as a trusted strategic partner to senior leaders, bringing together different perspectives and enabling collective decisions on issues that transcend individual business units.
Build trusted relationships with VP- and SVP-level leaders across PlayStation and Sony Group.
Facilitate high-stakes strategic conversations involving competing priorities, resource constraints, and differing perspectives on the future.
Use rigorous analysis (both internal and external), commercial judgment, and compelling narratives to influence decisions without relying on formal authority.
Help executive teams move from conceptual agreement to explicit decisions, accountable ownership, and coordinated action.
Challenge established assumptions constructively while demonstrating respect for the achievements and operational realities of existing businesses.
Identify and resolve strategic misalignment before it becomes an impediment to execution.
Develop the Core / Explore Strategic Framework
Support the development of two distinct but interconnected operating models that allow PlayStation to maximize current business performance while investing in future opportunities.
Establish differentiated frameworks for evaluating core-business optimization and higher-uncertainty exploration initiatives.
Help define how future opportunities are identified, validated, incubated, prioritized, and transitioned into scaled operating businesses.
Partner with Finance and operating leaders to develop portfolio-level investment frameworks that balance near-term returns with longer-term strategic value.
Create transparent decision criteria for advancing, redirecting, or discontinuing strategic initiatives.
Ensure exploration activities are commercially grounded without subjecting early-stage opportunities to inappropriate mature-business performance expectations.
Support leadership in determining where shared capabilities, resources, and partnerships can accelerate both operating systems.
Strengthen Enterprise Strategy Execution and Organizational Capability
Create repeatable approaches that allow SIE leaders to turn strategic direction into coordinated organizational progress.
Develop executive-level strategy activation frameworks, including strategic outcome maps, decision rights, leadership commitments, and progress measures.
Partner with team members to create processes for translating strategic choices into functional priorities without creating unnecessary reporting or bureaucracy.
Facilitate leadership working sessions that resolve trade-offs and create durable ownership of agreed outcomes.
Build strategy toolkits and practical methodologies that functional teams can adopt independently.
Capture and institutionalize lessons from strategic initiatives, including successes, unsuccessful experiments, and changing market assumptions.
Introduce AI-enabled research, synthesis, scenario modeling, and knowledge-management capabilities that increase the speed and quality of strategic work.
Required Experience and Qualifications
The ideal candidate will bring 15+ years of progressive experience in enterprise strategy, business transformation, corporate development, strategic operations, or product leadership, including substantial experience influencing senior executives within complex global organizations.
A proven record of leading enterprise-wide strategic transformation, with tangible examples of changes adopted by business leaders and sustained beyond the initial initiative.
Deep experience influencing cross-functional leadership teams, particularly in situations involving ambiguous authority, competing priorities, and significant organizational complexity.
Demonstrated success designing and implementing strategic planning, portfolio management, or governance frameworks that improved actual business decisions.
Experience in technology platforms, gaming, digital entertainment, consumer ecosystems, or similarly dynamic industries.
Strong commercial and financial judgment, including the ability to evaluate investment trade-offs, growth opportunities, and long-range enterprise value.
Exceptional executive communication, facilitation, and strategic storytelling capabilities.
Experience navigating global organizations and multicultural leadership environments.
Demonstrated ability to use emerging AI and analytical capabilities to improve strategic effectiveness.
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.
$275,000
—
$412,400 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: San Francisco
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
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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: Remote
Workplace: Remote
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
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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: London
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
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
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-DZ1
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: 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
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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: San Francisco
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
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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: London
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
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
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-DZ1
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: Remote
Workplace: Remote
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
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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: 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
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 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-DZ1
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, Vancouver, BC
Workplace: OnSite
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.
Location: Vancouver, Canada
Employment Type: Full-Time, 6-Month Fixed-Term Contract
Work Arrangement: On-Site
ABOUT THE ROLE
We are looking for a Robotics Test & Validation Engineer to join our Vancouver team on a 6-month, full-time fixed-term contract, supporting the testing, characterization, and validation of advanced robotic components and subsystems.
You will work hands-on with robotic actuators, joints, mechanisms, grippers, and dexterous robotic hands, helping ensure that our hardware meets performance, reliability, and safety requirements.
Working closely with Mechanical, Electrical, Controls, and Embedded Software engineers, you will develop and execute test procedures, build test fixtures, analyze performance data, and contribute to continuous design improvements.
This position offers the potential to transition into a permanent, full-time role based on individual performance, business needs, and future opportunities within the team.
This is an exciting opportunity for an early-career or intermediate engineer to gain hands-on experience in robotics testing, actuator characterization, automated validation, and hardware development while learning from experienced robotics professionals.
WHAT MAKES THIS ROLE EXCITING
- Work hands-on with advanced humanoid robotic hardware, including actuators, joints, grippers, and dexterous robotic hands.
- Develop and execute tests that directly influence the performance, reliability, and safety of next-generation humanoid robots.
- Gain practical experience in actuator characterization, sensor calibration, motor control, and automated testing.
- Build and improve custom test rigs and validation systems for complex electromechanical components.
- Collaborate with a multidisciplinary robotics team spanning mechanical, electrical, controls, and embedded software.
- See your testing and engineering insights directly contribute to real robotic hardware improvements.
WHAT YOU’LL DO
- Design, plan, and execute test procedures for robotic actuators, joints, mechanisms, grippers, and robotic hands, ensuring performance against engineering requirements.
- Build, assemble, and maintain test fixtures, test rigs, and measurement setups for functional, dynamic, endurance, and reliability testing.
- Perform actuator and sensor calibration, including encoders and motor control loops for current, velocity, and position, under the guidance of Controls engineers.
- Support actuator and subsystem characterization, measuring parameters such as torque output, friction, inertia, backlash, stiffness, thermal behavior, efficiency, and backdrivability.
- Develop and improve automated test procedures and hardware/software test setups to evaluate motor performance, force output, operating limits, and system reliability.
- Conduct lifecycle, stress, thermal, endurance, and environmental testing on robotic components and subsystems.
- Collect, analyze, and interpret test data, identifying performance trends, anomalies, and potential failure modes.
- Prepare clear test reports, performance summaries, and validation documentation, communicating findings to engineering teams.
- Work closely with Mechanical, Electrical, Controls, and Embedded Software engineers to identify root causes of hardware failures and support design improvements.
- Collaborate with design engineers to define testable requirements, acceptance criteria, tolerances, and performance metrics.
- Support incoming quality inspections, assembly-level verification, and hardware troubleshooting.
- Assist with closed-loop actuator testing, evaluating system behavior, stability, and response under different operating conditions.
- Maintain organized test documentation, procedures, results, and equipment records.
- Contribute to improvements in testing efficiency, automation, repeatability, and validation processes.
WE’RE LOOKING FOR
- 1–4 years of relevant hands-on experience in robotics testing, hardware validation, mechatronics, electromechanical systems, or a related technical field.
- Bachelor's degree or technical diploma in Mechanical Engineering, Electrical Engineering, Mechatronics, Robotics, or a related discipline, or equivalent practical experience.
- Hands-on experience testing, troubleshooting, or validating mechanical, electrical, or electromechanical systems.
- Understanding of electric motors, actuators, sensors, mechanical mechanisms, and basic control systems.
- Experience working with laboratory and measurement equipment, such as oscilloscopes, multimeters, power supplies, force sensors, and data acquisition systems.
- Familiarity with test procedures, data collection, performance measurements, and technical reporting.
- Basic understanding of motor control principles, including current, velocity, and position control.
- Experience with Python, MATLAB, LabVIEW, or similar tools for test automation, data analysis, or engineering calculations.
- Ability to read and interpret mechanical drawings, electrical schematics, and technical documentation.
- Strong analytical and practical problem-solving skills, with the ability to identify issues and support troubleshooting activities.
- Good attention to detail when performing precision measurements, calibration, and hardware testing.
- Ability to collaborate effectively with Mechanical, Electrical, Controls, and Embedded Software engineering teams.
- Comfortable working in a fast-paced R&D environment with evolving hardware designs and testing priorities.
WHAT WE OFFER
- Enjoy a modern Vancouver office environment with complimentary daily lunches, coffee, tea, soft drinks, and snacks.
- Gain hands-on experience developing next-generation humanoid robots.
- Opportunity for long-term career growth, with the potential to transition from a 6-month fixed-term contract into a permanent, full-time position.
- Work directly with advanced robotic hardware and complex electromechanical systems.
- Learn from a highly experienced, multidisciplinary robotics engineering team.
- Contribute to real engineering projects, from prototype assembly through testing and validation.
- Build valuable technical experience in a fast-paced robotics startup environment.
- Join a collaborative, mission-driven team working at the forefront of humanoid robotics.
Location: Dallas; Austin; Houston
Workplace: Remote
THE ROLE
As an Enterprise Solutions Architect at ClickHouse, you'll own the technical side of the sales cycle for enterprise accounts in Texas. This role serves our Enterprise segment in Texas, and the ideal candidate would be based in Austin or Dallas.
You'll engage with data platform engineers, architects, SRE, and the VP who owns the standard - and your job is to design something that satisfies all of them and then prove it at production scale.
Getting an enterprise team there usually means moving them off something else, so most of your work is making that migration credible: the architecture, benchmarks run against their own data, and a plan their engineers believe they can execute.
This is a role for engineers who want the hard version of the problem: real scale, real constraints, and an incumbent to displace. Prior pre-sales experience helps but isn't required - technical depth is non-negotiable.
WHAT YOU WILL BE DOING
- Own the technical evaluation for enterprise accounts - from discovery through POC or competitive bake-off, architecture sign-off, security review, and first production workload.
- Engage across a wider set of stakeholders than a single team: data platform engineers, architects, SRE, security, and the executive who owns the standard. Design solutions that hold up with all of them in the room.
- Design for production scale - sizing, sharding and replication strategy, ingestion topology, tiered storage, cost modeling, and what happens when something fails at 3am.
- Win competitive displacements against Elasticsearch, Splunk, Snowflake, BigQuery, Druid, Pinot, and homegrown systems, using benchmarks the customer's own team can reproduce.
- Own the migration plan - sequencing, dual-run, validation, and cutover - so the customer's team can see exactly how they get to production.
- Clear the security and procurement path: questionnaires, compliance artifacts, network and identity architecture, and BYOC or private deployment requirements.
- Partner closely with Enterprise AEs to progress and close opportunities - you own the technical win, they own the commercial close. Build the TCO case against the incumbent/competition together.
- Advocate for customer needs internally with Product and Engineering - you're the voice of the technical buyer inside ClickHouse.
- Contribute reference architectures, benchmark harnesses, migration guides, and objection handling material that help the team scale what's working.
WHAT YOU BRING
- Deep technical foundation in data infrastructure - built through experience as a data engineer, platform engineer, software engineer, DBA, or solutions architect.
- Production experience with analytical databases (ClickHouse, Snowflake, BigQuery, Redshift, Druid, Pinot, Vertica) and with operating them, not just querying them.
- Distributed systems judgment: partitioning, replication, consistency trade-offs, query execution, and a felt sense for where things break under load.
- Fluency across the modern data stack - Kafka and CDC pipelines, orchestration, object storage, BI tools, and at least one major cloud (AWS, GCP, Azure) at architecture level.
- Experience running a technical evaluation against a named competitor and winning it, including designing the migration off the incumbent and the parts of it that are genuinely hard.
- Customer-facing experience with real stakes - pre-sales, consulting, technical account management, or a staff-level engineering role that put you in front of customers.
- Strong written and verbal communication. You can whiteboard with a staff engineer in the morning and present to a VP of Engineering in the afternoon.
- Comfort with longer cycles and more stakeholders. Enterprise evaluations don't close in three weeks, and you know how to keep one moving without letting it stall.
- Willingness to say ClickHouse isn't the right tool for a given workload when that's true.
PERKS
- Flexible work environment - ClickHouse is a globally distributed company and remote-friendly. We currently operate in over 25 countries.
- Healthcare - Employer contributions towards your healthcare.
- Equity in the company - Every new eligible team member who joins our company receives equity.
- Time off - Flexible time off in the US, generous entitlement in other countries.
- A USD$500 Home office setup if you’re a remote employee.
- Global Gatherings – We believe in the power of in-person connection and offer opportunities to engage with colleagues at company-wide offsites.
CULTURE - WE ALL SHAPE IT
As part of a rapidly scaling start-up, you will be instrumental in shaping our culture.
Are you interested in finding out more about our culture? Learn more about our values here https://clickhouse.com/company/careers. Check out our blog posts https://clickhouse.com/blog or follow us on LinkedIn https://www.linkedin.com/company/clickhouseinc/life/0c1ee7f4-2129-488d-b413-e7f6270659fd/?viewAsMember=true to find out more about what’s happening at ClickHouse.
EQUAL OPPORTUNITY & PRIVACY
ClickHouse provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Please see here https://clickhouse.com/legal/applicant-privacy-notice for our Privacy Statement.
Location: San Francisco
Asana is hiring a Head of IT Systems Engineering to lead the team that powers how every Asana employee works. Reporting to the Head of IT, this San Francisco-based leader owns the strategy, architecture, and operations behind our SaaS productivity applications, corporate endpoints, identity, and user lifecycle, setting the standards and roadmap that keep every employee secure and productive. You will also influence the way Asana evaluates, adopts, and governs the tools and platforms our employees rely on. You will be responsible for the Client Platform Engineering, Application Engineering, and Identity & Integrations teams, who deliver this work. This role has one manager level report.
You ask good questions, are confident in not knowing everything, and would rather build with others than go it alone. You are crisp and detail oriented, but comfortable working outside the boundaries when the situation calls for it. You bring a proven record of success, a passion for technology, and, like us, you value hard work and fun in equal measure.
This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
What you’ll achieve
Develop the multi-year vision, roadmap, and architecture for Systems Engineering, aligned with Asana’s business priorities and Asana’s broader AI strategy
Accelerate an Agentified Asana, helping teams across Asana embrace our tools and reduce the friction of manual work.
Partner with leaders across Asana to build and maintain an efficient and effective portfolio of SaaS tools to enable all Asanas to do their best work.
Lead, develop, and grow the Client Platform Engineering, Application Engineering, and Identity & Integrations teams, including hiring, performance management, succession planning, and career development
Own the strategy and operation of corporate endpoint management, SaaS application management, identity, and the full user lifecycle
Drive IT’s AI strategy, from evaluating and governing platforms such as Claude, Gemini, and OpenAI to building AI agents and automation for onboarding, access requests, support, and compliance workflows
Partner with Security, Legal, and Privacy to set AI usage policies, data access controls, and vendor risk standards, including identity-based access and data loss prevention for AI tools and integrations
Set client platform standards and drive excellence in system performance, patching, and configuration compliance
Partner with IT Support, IT Infrastructure, and Security leadership to resolve issues, reduce risk, and improve the employee experience
Represent Systems Engineering to senior stakeholders, communicating priorities, tradeoffs, and results clearly
About you
10+ years of IT experience, including 5+ years directly leading teams of systems engineers and software engineers in a fast-paced, cloud-first environment
Proven ownership of purchasing, inventory management, and budgeting at scale
Strong, hands-on knowledge of current IAM practices and cloud-based identity, SSO, SAML, and SCIM
Experience with hosted cloud applications, including Okta, Google Workspace, Asana, Figma, and Slack
Experience establishing governance for emerging technology, including AI usage policy, data protection, and vendor risk review
Track record of setting strategy and roadmaps, then delegating effectively while staying close enough to the details to coach and unblockExperience with configuration management and automation tools such as JAMF, Intune, Puppet, and Munki
Working knowledge of scripting and API integration (REST, OAuth, Python, PowerShell, Bash, or equivalent)
Hands-on experience with enterprise AI platforms such as Claude, and OpenAI, including deployment, administration, and integration through APIs, connectors, and MCP servers
Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making
How you work
A strong mix of problem solving and a positive, service-oriented attitude
Excellent communication and documentation skills, with the ability to influence senior stakeholders and cross-functional partners
Curiosity and a bias toward experimenting with AI in your own work, and the ability to lead a team through rapid change
At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
What we’ll offer
Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
For this role, the estimated base salary range is between $252,000 - $296,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.
We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
Mental health, wellness & fitness benefits
Career coaching & support
Inclusive family building benefits
Long-term savings or retirement plans
In-office culinary options to cater to your dietary preferences
These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your recruiter to learn more about the total compensation and benefits for this role.
#LI-Hybrid #LI-SA
About us
Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law.
Join Asana’s Talent Network
to stay up to date on job opportunities and life at Asana.
Location: Distributed
About Us
At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.
At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.
Available Locations:
Montreal, QC
Professional working proficiency in French & English (written and spoken) is required.
(Compétence professionnelle complète en français, à l'oral et à l'écrit, requise.)
What you will do as a Customer Engineer
The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey.
Key Responsibilities
Technical Validation:
Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. . Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals.
Customer Adoption & Value Realization:
Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices. Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk.
Commercial Accountability & Expansion:
Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives.
Trusted Advisory:
Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes.
AI Orchestration & Workflow Automation:
Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory.
Education & Enablement:
Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization.
Minimum Qualifications
Professional working proficiency in French & English (written and spoken) is required.
(Compétence professionnelle complète en français, à l'oral et à l'écrit, requise.)
Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services, Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling).
Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly.
Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives.
Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles.
Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy.
Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below:
Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS.
Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts.
Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3.
AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows.
Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions.
Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments.
Strongly Preferred Qualifications (The "Good-to-Haves")
Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms.
Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls.
Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2.
Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth.
Education
Undergraduate or graduate degree in Computer Science, Engineering, or a related field.
Travel
This role will require travel up to 20–50% to attend customer meetings, conferences, industry events, and other in-person team meetings, within the assigned territory. For this reason, candidates must have reliable personal or local public transportation to complete all required travel. Required travel is reimbursable in accordance with the Company's Travel & Expense Policy, as it may be amended from time to time.
What Makes Cloudflare Special?
We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.
Project Galileo
: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.
Athenian Project
: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.
1.1.1.1
: We released
1.1.1.1
to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our
privacy commitment
and ensure that no user data is sold to advertisers or used to target consumers.
Sound like something you’d like to be a part of? We’d love to hear from you!
Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process.
This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.
Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual
race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law.
We are an AA/Veterans/Disabled Employer.
Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at
hr@cloudflare.com
or via mail at 101 Townsend St. San Francisco, CA 94107.
Location: Amsterdam, Netherlands
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
Acts as the senior Rewards Business Partner and connective layer between Nebius' global Rewards operating model and its global Infrastructure organization. Owns delivery of company-wide rewards programs into Infrastructure, ensuring effective execution, adoption, and alignment with global principles, governance, and controls. Brings deep understanding of Infrastructure priorities, talent needs, and external market trends to proactively recommend evidence-based improvements or adaptations. Any changes are developed with global program owners and agreed through established governance, preserving one coherent Nebius operating model.
Key Responsibilities:
Owns end-to-end delivery of Nebius' global rewards programs for Infrastructure, translating enterprise frameworks into clear plans, decisions, communications, and manager actions that work effectively for the organization.
Serves as a trusted advisor to senior Infrastructure leaders, HR Business Partners, and Talent Acquisition, balancing strong advocacy for Infrastructure needs with stewardship of company-wide consistency, fairness, affordability, and governance.
Leads evaluation of new and evolving Infrastructure roles within Nebius' global job architecture, recommending grade, salary range, incentive opportunity, and equity treatment and escalating genuine framework gaps to the relevant global owners.
Leads Infrastructure delivery across merit, bonus, and equity cycles, coordinating global timelines and requirements, guiding leadership calibrations, resolving complex issues, and ensuring accurate, equitable, and on-budget outcomes.
Monitors external market trends and internal Infrastructure workforce data across geographies, roles, pay mix, and incentive practices; identifies emerging gaps and converts the evidence into practical recommendations for global program owners.
Applies Nebius' global equity frameworks across Infrastructure, ensuring consistent treatment while surfacing evidence-based proposals for geographic, performance, or critical-talent differentiation through the appropriate governance channels.
Builds and scales local compensation policies as Infrastructure expands into new countries and regions, ensuring new-market pay practices align with global governance while reflecting local market realities.
Develops executive insights on pay positioning, incentive outcomes, equity value, budget impact, hiring trends, and retention risk, connecting Infrastructure-specific signals to enterprise priorities and clear decisions.
Tracks delivery, adoption, and effectiveness of rewards programs in Infrastructure, identifies structural pay, incentive, compression, or equity risks, and leads corrective action with global program owners and business stakeholders.
Acts as the two-way bridge between Infrastructure and global Rewards: brings business insight into enterprise design, influences priorities and practical adaptations, and translates, supports, and explains global approaches within Infrastructure. Leads manager enablement and guides less experienced rewards professionals.
Requirements:
Extensive progressive experience in compensation or total rewards, including substantial business-partnering experience with Engineering, Infrastructure, or other technical functions in a complex multinational organization.
Advanced, wide-ranging knowledge of base salary, equity programs, market pricing, job evaluation, and annual compensation planning, with depth in technical/infrastructure reward models and international, multi-country pay practices.
Advanced analytical and financial modeling skills, with the ability to evaluate ambiguous variables, assess business and cost implications, and turn complex data into clear executive recommendations.
Demonstrated success influencing and constructively challenging senior stakeholders while balancing business advocacy with enterprise stewardship, global consistency, and sound governance.
Executive-level communication, consulting, and facilitation skills, with the ability to align diverse stakeholders and explain sophisticated rewards concepts with clarity and commercial relevance.
Experience owning delivery of cross-functional rewards programs in a matrixed global model and using compensation, market, and business intelligence tools to drive scalable outcomes.
Experience in a publicly listed, global, fast-growing technology or AI organization preferred; experience guiding other rewards professionals and a Certified Compensation Professional (CCP) designation are advantageous.
#LI-CH1
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
United States of America
УдалённоUnited States; Support a global workforce with legal counsel that works across borders, cultures, and time zones; If you’ve supported teams across borders in-house, you’ll have a head start with a company that works across time zones and jurisdictions
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