Location: 2405 Satellite Boulevard Suite 200, Duluth, GA 30096
Come join our team!
There are many reasons why EPIC Insurance Brokers & Consultants has become one of the fastest-growing firms in the insurance industry. Fueled and driven by capable, committed people who share common beliefs and values and “bring it” every day, EPIC is always looking for people who have “the right stuff” – people who know what they want and aren’t afraid to make it happen.
Headquartered in San Francisco and founded in 2007, our company has over 3,000 employees nationwide. With locations spread out across the U.S., our local market knowledge and industry expertise helps support our clients' regional and global needs. We have grown very quickly since our founding, and we continue to see growth and success thanks to our hard-working and growth-minded employees.
Our core values are: Owner mindset, Inspire trust, Think big, and Drive results. If these values and growth align with what you're looking for in your next career? Then consider joining our amazing team!
LOCATION:
Duluth, Georgia, hybrid role- 3 days a week in the office.
JOB OVERVIEW:
The Account Manager serves as the primary day-to-day contact for employee benefits clients, delivering exceptional service and support throughout the client lifecycle. This role partners closely with Client Executives, carriers, internal departments, and clients to ensure a seamless experience while helping clients navigate benefits administration, compliance, enrollment, billing, and employee benefits programs.
What You'll Do:
Client Service & Account Management
Serve as the primary day-to-day contact for assigned clients and build strong, trusted relationships.
Partner with clients, Client Executives, and internal teams to execute comprehensive service plans.
Coordinate and support open enrollment meetings, including preparation of employee communication materials.
Complete COBRA paperwork for new group implementations and renewals.
Maintain ongoing client communication regarding benefit trends, legislative changes, and regulatory updates.
Collaborate with compliance specialists and Client Executives to support government reporting requirements and compliance initiatives.
Maintain accurate client and benefits plan information within EPIC's CRM system.
Resolve enrollment, eligibility, and basic claims issues while coordinating escalated claims with the claims department.
Research and resolve billing discrepancies and administrative concerns.
Keep Client Executives informed of client issues, concerns, and significant events.
Participate in mentorship, training, and professional development activities.
Operational Excellence
Work closely with Client Executives to prioritize activities and manage workflows effectively.
Maintain client documentation, activity logs, and agency management system records.
Communicate professionally and collaborate effectively with colleagues, clients, and carrier partners.
Stay current on industry developments, market trends, product offerings, legislation, and technology advancements.
Consistently project a professional and customer-focused image.
What You'll Bring
Working knowledge of employee benefits programs, including:
Fully insured plans
Self-funded plans
Level-funded plans
Strong proficiency with Microsoft Office applications, including Outlook, Word, Excel, and PowerPoint.
Excellent organizational skills with exceptional attention to detail.
Strong time management and ability to manage multiple priorities in a fast-paced environment.
Ability to work independently and collaboratively within a team setting.
Effective written and verbal communication skills.
Experience using agency management systems, HR portals, and related technology platforms.
High school diploma required; some college coursework preferred.
Minimum of 2 years of employee benefits account management experience with a brokerage, consulting firm, insurance carrier, TPA, or related organization.
Demonstrated ability to manage competing deadlines while maintaining a high level of service.
Strong professionalism, discretion, diplomacy, and ability to handle confidential information.
Licenses & Certifications
Georgia or Indiana Life & Health License, or ability to obtain within 60 days of hire.
Valid driver's license.
COMPENSATION:
The base pay offered will be determined based on your experience, skills, training, certifications and education, while also considering internal equity and market data.
WHY EPIC:
EPIC has over 60 offices and 3,000 employees nationwide – and we’re growing! It’s a great time to join the team and be a part of this growth. We offer:
Generous Paid Time off
Managed PTO for salaried/exempt employees (personal time off without accruals or caps); 22 PTO days starting out for hourly/non-exempt employees; 12 company-observed paid holidays; 4 early-close days
Generous leave time options: Paid parental leave, pregnancy disability and bonding leave, and organ donor/bone marrow donor leave
Generous employee referral bonus program of $1,500 per hired referral
Employee recognition programs for demonstrating EPIC’s values plus additional employee recognition awards and programs (and trips!)
Employee Resource Groups: Women’s Coalition, EPIC Veterans Group
Professional growth & development: Mentorship Program, Tuition Reimbursement Program, Leadership Development
Unique benefits such as Pet Insurance, Cancer Insurance, Identity Theft & Fraud Protection Coverage, Legal Planning, Family Planning, and Menopause & Midlife Support
Additional benefits include (but are not limited to): 401(k) matching, medical insurance, dental insurance, vision insurance, and wellness & employee assistance programs
50/50 Work Culture: EPIC fosters a 50/50 culture between producers and the rest of the business, supporting collaboration, teamwork, and an inclusive work environment. It takes both production and service to be EPIC!
EPIC Gives Back – Some of our charitable efforts include Donation Connection, Employee Assistance Fund, and People First Foundation
We’re in the top 10 of property/casualty agencies according to “Insurance Journal”
To learn more about EPIC, visit our Careers Page:
https://www.epicbrokers.com/about/epic-careers/
.
EPIC embraces diversity in all its various forms—whether it be diversity of thought, background, race, religion, gender, skills or experience. We are committed to fostering a work community where every colleague feels welcomed, valued, respected and heard. It is our belief that diversity drives innovation and that creating an environment where every employee feels included and empowered, helps us to deliver the best outcome to our clients.
California Applicants - View your privacy rights at:
https://www.epicbrokers.com/wp-content/uploads/2025/01/epic-ca-employee-privacy-notice.pdf
.
#LI-SG1
#Hybrid
Location: New York
Who We Are:
Galaxy Digital Inc. (Nasdaq: GLXY) is a global leader in digital assets and data center infrastructure, growing the economy that runs on code. Galaxy delivers the onchain infrastructure that connects institutions to digital assets, including trading, advisory, asset management, staking, self-custody, and tokenization. Galaxy also develops and operates data center infrastructure to power AI and HPC workloads. Anchored by its Helios campus in Texas, Galaxy is building a multi-gigawatt pipeline of more than 5.7 GW of potential capacity, positioning it among the largest and fastest-growing data center developers in North America.
The Company is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.
Additional information about Galaxy's businesses and products is available on
www.galaxy.com
.
What We Value:
We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.
Seek Excellence.
Be Selective To Be Effective.
Be Highly Aligned, Loosely Coupled.
Disagree Transparently.
Encourage Independent Decision-Making.
Build Dream Teams.
About the Galaxy Summer Internship Program
The Galaxy NYC Summer Internship Program is an immersive, nine-week experience taking place on-site in our New York HQ office. During the nine weeks, you will gain hands-on, practical work experience on our Investment Banking, working on real products and problems alongside the people building them.
Interns join a lean team advising crypto and fintech companies on M&A, capital raising, and corporate strategy.
In addition to learning on the job, Galaxy interns participate in professional development programming, social events, and networking opportunities with senior leaders.
Program Dates
:
June 7th – August 6th, 2027
What You'll Do:
Build and review financial analyses and valuation models, including comparable companies, precedent transactions, DCF, and merger models.
Research companies and protocols using public filings, earnings calls, industry research, and onchain data.
Map buyer and investor universes, analyze competitive landscapes, and assess business models and value drivers.
Prepare pitch materials, management presentations, teasers, and internal committee memos.
Support live deals through preparation, data room maintenance, and process tracking.
Use AI tools to accelerate research and analysis, improve internal processes, and help develop AI-enabled workflows and agents.
What We're Looking For:
A genuine interest in crypto and investment banking, demonstrated through independent research, coursework, projects, or relevant experience.
Initiative, intellectual curiosity, and sound judgement, with the ability to work through unfamiliar problems and ask thoughtful questions.
Strong analytical skills and a foundational understanding of accounting, corporate finance, and valuation.
Familiarity with blockchain technology, token economics, and how value accrues to companies, protocols, and tokens.
Strong attention to detail, a collaborative approach, and the ability to manage competing deadlines.
Clear, concise written and verbal communication, and the ability to simplify complex ideas.
Bonus Points:
Previous internship or work experience in crypto or investment banking.
Financial or valuation models for companies, tokens, or protocols.
Experience using AI tools beyond chat interfaces, including APIs, agents, or automated research and analysis workflows.
Published writing, research or other work demonstrating original thinking about crypto businesses, protocols, or markets.
Programming or data analysis experience (Python, SQL).
Eligibility Requirements:
Currently enrolled in an undergraduate degree program, with an expected graduation date between December 2027 and June 2028.
Available to work on-site in New York City five days a week for the full program, June 7 – August 6, 2027.
Students enrolled in PhD or JD programs are not eligible to apply.
Here are some of the industry-leading benefits of interning at Galaxy:
Opportunities to learn about the Digital Asset and Data Center industry
Free daily snacks and weekly lunches
Smart, entrepreneurial and fun colleagues
Employee Resource Groups
*Benefits may vary based on location.
Interns are classified as non-exempt employees and will be paid a rate of $55/hr.
Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances.
We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact
careers@galaxy.com.
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: 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: 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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows.
- Design and run post-training experiments across SFT and RL, building on leading open-weight models.
- Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break.
- Run and debug training at scale, addressing divergence, reward hacking, and instability.
- Build and use rigorous evals to track improvements and decide what ships.
- Design, implement, test, and debug code across our research stack.
WHAT YOU HAVE
- Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results.
- Deep ML fundamentals and experience getting distributed training runs working reliably.
- Strong engineering skills in Python, with production-quality code and end-to-end system ownership.
- Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required.
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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows.
- Design and run post-training experiments across SFT and RL, building on leading open-weight models.
- Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break.
- Run and debug training at scale, addressing divergence, reward hacking, and instability.
- Build and use rigorous evals to track improvements and decide what ships.
- Design, implement, test, and debug code across our research stack.
WHAT YOU HAVE
- Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results.
- Deep ML fundamentals and experience getting distributed training runs working reliably.
- Strong engineering skills in Python, with production-quality code and end-to-end system ownership.
- Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required.
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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows.
- Design and run post-training experiments across SFT and RL, building on leading open-weight models.
- Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break.
- Run and debug training at scale, addressing divergence, reward hacking, and instability.
- Build and use rigorous evals to track improvements and decide what ships.
- Design, implement, test, and debug code across our research stack.
WHAT YOU HAVE
- Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results.
- Deep ML fundamentals and experience getting distributed training runs working reliably.
- Strong engineering skills in Python, with production-quality code and end-to-end system ownership.
- Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required.
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 own 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 post-training recipe across SFT and RL, including reward design and verification for challenging, semi-verifiable legal tasks. You’ll help set the research direction and carry ideas from experiments through training runs to models used by customers. 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 and scientists who have gotten training runs working at scale, are immersed in RL for language models, and want their work to reach users quickly.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Own and pursue a research agenda to improve model capability on long-horizon legal reasoning and agentic workflows.
- Design and run post-training experiments across SFT and RL, building on leading open-weight models.
- Develop reward functions and verifiers for semi-verifiable tasks, including rubrics, learned preference models, and expert preference data, and study where they break.
- Run and debug training at scale, addressing divergence, reward hacking, and instability.
- Build and use rigorous evals to track improvements and decide what ships.
- Design, implement, test, and debug code across our research stack.
WHAT YOU HAVE
- Hands-on experience post-training LLMs with SFT and RL, including preference optimization, and direct ownership of training runs and results.
- Deep ML fundamentals and experience getting distributed training runs working reliably.
- Strong engineering skills in Python, with production-quality code and end-to-end system ownership.
- Research experience in RL for language models or reward modeling, with the ability to move quickly from experiments to shipped improvements. Publications welcome, not required.
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, CA • New York, NY • United States
Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
We’re looking for a strategic, entrepreneurial Product Manager to help shape the future of Collab Tools. Collab Tools includes FigJam, Figma Slides, and Figma Specs. You’ll be at the forefront of defining how product teams plan, capture intent, and communicate: from the initial brainstorm to the functional prototype. As we integrate AI to make these workflows more intuitive and powerful, you’ll help us build the next generation of surfaces that empower teams to align and execute faster than ever.
What you’ll do at Figma:
Own the strategy and roadmap for one of our key products (e.g. FigJam), and help drive our vision of Collab Tools as the defacto surfaces for upstream planning and discovery.
Partner deeply with Design and Engineering to ship both foundational improvements and 0-to-1 bets, holding a high bar for craft and consumer-grade quality.
Synthesize quantitative, qualitative, and market signals into a sharp point of view on what to build and why.
Build durable relationships across your direct team, the broader pillar, and cross-functional partners, including the executive team.
Define and run agent evals defined by our vision and grounded in real user behavior to measure and improve quality, latency, and cost.
Push the frontier of AI-native product development in what you ship and in how the team plans and builds.
Operate your area end-to-end, from long-term strategy through launch and iteration, moving fast without dropping standards.
We’d love to hear from you if you have:
5-7+ years of product management experience, with a track record of shipping meaningful, well designed, consumer-grade products at B2B companies.
Comfort with ambiguity and a demonstrated ability to develop and defend a clear point of view.
Hands-on experience building and shipping agentic experiences, including defining evals, designing applied AI products, and navigating tradeoffs around quality, reliability, latency, and cost.
Fluency with the latest AI tools and genuine curiosity and excitement about how EPD teams are changing because of them.
A track record of moving fast, even inside a larger organization.
Fluency across quantitative, qualitative, and market signals to fuel prioritization and decisions.
Strong communication and organizational skills at every level, from IC to executive.
While it’s not required, it’s an added plus if you also have:
Previous experience in an engineering or design role, deeper technical chops, or interesting side projects.
Experience at both a smaller company and a more mature, late-stage or public company.
At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Pay Transparency Disclosure
Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location.
Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law.
Annual Base Salary Range:
$169,000
—
$303,000 USD
At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an
equal opportunity workplace
- we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
,
or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to
accommodations-ext@figma.com
. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
Examples of accommodations include but are not limited to:
Holding interviews in an accessible location
Enabling closed captioning on video conferencing
Ensuring all written communication be compatible with screen readers
Changing the mode or format of interviews
To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with
Figma's Candidate Privacy Notice
.
Application limits:
To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles:
Candidates may submit up to 5 applications during any rolling 30-day period.
Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection.
Once the applicable days has passed, candidates are welcome to apply again.
Location: Hybrid
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.
Location: Austin, TX
About the Role
We are seeking a Data Center Design Engineer to design Cloudflare’s pending and future infrastructure deployments for generational improvement in cost, quality, and speed of deployment. In this role, you will lead electrical design and end-to-end execution for new sites, expansions, and infrastructure upgrades supporting compute, storage, and high-density liquid-cooled GPU deployments. We are looking for someone who excels at progressing many projects in parallel, managing dynamic day-to-day priorities with many stakeholders, and serving as Cloudflare's owner's representative to refine data center design best practices in a high-growth environment. Getting stuff done is a must!
The Data Center Strategy team is part of Cloudflare’s global Infrastructure (INF) team. The INF team grows and manages Cloudflare’s global data center/PoP footprint, enabling Cloudflare’s tremendous growth with compute, network, and data center infrastructure, utilizing an extensive range of global partner vendors.
What you'll do:
Translate data center capacity requirements into actionable white space design and/or rack plans within individual data center contract constraints for power, coolingManage implementation phase of cage projects with data center providersDesign low voltage structured cabling, fiber, cross-connect & conveyance infrastructure as well as any supporting infrastructure on the data center ceiling/floorWork with supply chain team on rack integration plans and location deployment qualification
Work cross-functionally with Cloudflare data center engineering team and other internal teams (capacity planning, network strategy, security) to verify scope and solution and create repeatable standard installation procedures
Take ownership of and lead projects to design and implement data center expansions or new data centers on tight deadlines with minimal oversight
Technical support in negotiations with external data center partners
Assist in RFP preparation, review and cost/engineering analysis
Review one-line diagrams and cooling equations for new and existing data centers (Data Center M&E)
Power component (PDU) review/approval for Hardware sourcing team
Implement, document and maintain power consumption tracking tools and fulfil ad-hoc reporting requests
Research new and innovative power efficiency technologies and programs
Travel up to 25% to perform infrastructure audits, validate data center construction work and buildouts, and participate in commercial processes.
Develop and execute modular and prefabricated data center construction strategies to accelerate time-to-market and optimize cost efficiency
Perform electrical short-circuit, coordination, arc flash, and load flow engineering studies to ensure system reliability and compliance
Other duties as assigned
Partner with Hardware Sourcing and SRE/Infrastructure teams to validate PDU specifications, rack integration plans, and power distribution topologies across global PoP footprints
Lead electrical design and end-to-end execution for new sites, expansions, and infrastructure upgrades from site qualification and basis of design through energization, commissioning, and operational handover
Serve as Cloudflare's electrical owner's representative, defining design criteria, scopes, deliverables, responsibility matrices, review gates, and acceptance requirements for data center operators, consulting engineers, contractors, commissioning agents, utilities, and vendors
Design and review utility-to-rack infrastructure, including utility service, transformers, switchgear, generators, UPS systems, transfer systems, modular and prefabricated electrical assemblies, busway, feeders, whips, rack PDUs, grounding, and metering
Define electrical interfaces and auxiliary-load requirements for direct-to-chip liquid cooling, coolant distribution units (CDUs), pumps, controls, leak detection, facility water systems, and heat-rejection equipment
Develop and review basis-of-design documents, single-line diagrams, specifications, equipment schedules, calculations, sequences of operation, and interface control documents
Oversee technical acceptance of FAT, SAT, Level 1–5 staged commissioning, integrated systems testing, failure-mode testing, deficiency closure, and turnover documentation
Define EPMS, metering, telemetry, and capacity-tracking requirements for operational power and capacity management
Requirements
Bachelors or equivalent experience plus 5+ years of experience in data center mechanical and electrical design and operations/deployment/installation, P.E. certification or equivalent a plus
Experience in HVAC, Chilled Water Systems, Condenser Water Systems, Pump controls, Glycool/Glycols, AHU units (DX, split, RTU, CRAC, etc.), CRAH, Raised Floor Systems, HOT/COLD aisle containment and Building Management Systems
Understanding of basic electrical theory (voltage, current, power), basic circuit design & analysis, and single- and three-phase power systems
Familiarity with Data Center M&E infrastructure design concepts, electrical/UPS topologies, cooling methodologies (central plant, room cooling, high density thermal strategies)
Familiarity with industry standards for resilient Data Center design and Uptime Institute Tier Classifications
Excellent verbal, written communication and presentation skills
Experience working with multiple time zones and multiple cross-functional teams
Experience working on time sensitive projects with delivery responsibility under pressure
Understanding of network hardware architecture, data center switching/routing infrastructure, and optical line/transceiver power and thermal profiles
Experience acting as an owner's technical representative, governing external delivery partners, reviewing third-party designs, resolving technical disputes, and driving noncompliance and project risks through documented closure
Expertise in medium- and low-voltage distribution, transformers, generators, UPS systems, switchgear, transfer systems, busway, grounding, protection, and rack-level power architectures for high-density deployments
Understanding of direct-to-chip liquid cooling and the electrical dependencies of CDUs, pumps, controls, facility water systems, and heat-rejection equipment
Experience with construction administration, equipment testing, energization planning, staged commissioning, integrated systems testing, deficiency management, and failure-mode testing
Experience with utility coordination, design-deviation governance, power-quality or incident investigations, and lifecycle management of mission-critical electrical infrastructure
Bonus Points
Degree in electrical/mechanical engineering or IT a plus
Experience in large-scale mission critical facility infrastructure design, construction, commissioning, and/or operations a plus
Experience with industry standards and building codes including NFPA 70/NEC, IEEE, NEMA, ANSI, UMC, ASHRAE, UBC, LEED, and Uptime Institute standards
Knowledge of programming languages a plus
JIRA, Confluence admin-level experience a plus
AutoCAD experience a plus
Experience with FLOTHERM or Tileflow a plus
Hands-on experience with hardware validation, power/cooling capacity modeling, or thermal simulation tools (such as FLOTHERM or Tileflow)
Familiarity with systems programming, scripting (Python, Go, or Bash), or automation workflows for power/infrastructure tracking
Experience with NVIDIA DGX, GB200/GB300 NVL, OCP Open Rack, or comparable liquid-cooled GPU platforms and AI factory reference architectures
Experience with ETAP, SKM PowerTools, EasyPower, or equivalent software for dynamic modeling, generator transient analysis, harmonic analysis, and UPS compatibility assessment
Experience with EPMS/BMS integration, branch-circuit monitoring, rack-level telemetry, metering, capacity forecasting, or automated infrastructure reporting
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: Remote
Workplace: Remote
Hi, we’re Gravie. Our mission is to create health benefits that actually benefit small and midsize businesses and their employees. Our innovative benefit solutions and services are developed and delivered by a diverse group of unique people. We encourage you to be your authentic self - we like you that way.
ABOUT THE ROLE
We are seeking a Director of Corporate Compliance and Privacy to lead and mature our healthcare compliance and privacy programs. This leader will build and coach two managers, one for compliance and one for privacy, who each lead a team of junior-level professionals. The Director will partner closely with clinical, operational, technology, and business leaders and apply sound judgment in a complex, fast-changing regulatory environment. You will be a trusted advisor who helps the organization deliver care and grow responsibly while protecting health plan members, their data, the organization's integrity, and its reputation.
KEY RESPONSIBILITIES
PROGRAM LEADERSHIP:
- Design, implement, and continuously improve the compliance program in line with the elements of an effective compliance program described in federal guidance (e.g., HHS-OIG), including policies, training, monitoring, auditing, and reporting
- Assess emerging healthcare regulatory and privacy risks and translate them into practical, risk-based controls
- Report regularly to executive leadership and the Board or Compliance Committee on program effectiveness, key risks, and trends
PRIVACY PROGRAM LEADERSHIP:
- Oversee the privacy program, including HIPAA Privacy Rule compliance, state health privacy and consumer data privacy laws, and privacy policies, notices, and training
- Direct privacy incident and breach response in coordination with Security, Legal, and business owners, including risk assessments and required notifications
- Oversee privacy reviews of new products, systems, vendors, and data uses, including privacy impact assessments and business associate agreements
- Oversee the health plan member rights request program, ensuring timely, compliant handling of requests for access, amendment, accounting of disclosures, restrictions, and confidential communications, in accordance with HIPAA and applicable state law.
- Serve as a point of contact for privacy regulators, and work with the Security Officer to align privacy and security controls
TEAM LEADERSHIP:
- Lead, develop, and hold accountable the Compliance Manager and the Privacy Manager, who each manage junior-level team members
- Coach and mentor both managers to build their leadership capability, set clear goals, and develop strong succession pipelines
- Set shared priorities and clear division of work between the compliance and privacy teams, and make sure they coordinate on overlapping issues
- Plan for resourcing, structure, and long-term capability of the function, including a distributed and remote team
CROSS-FUNCTIONAL PARTNERSHIP:
- Build and maintain trusted relationships across the organization
- Embed compliance and privacy considerations early into business processes and decisions as a collaborative partner rather than a gatekeeper
- Influence stakeholders at all levels, including senior executives and clinical leaders, without relying solely on formal authority
ENTERPRISE RISK MANAGEMENT:
- Operate the Compliance and Privacy programs as distinct risk levers within the purview of the Chief Compliance Officer, working in close coordination with Enterprise Risk Management and Internal Audit, and with business leaders, to integrate compliance and privacy risks into the enterprise risk framework.
- Identify and assess compliance and privacy risks and provide them to Enterprise Risk Management for inclusion in the enterprise risk register, coordinating with Internal Audit and business leaders to ensure risks are consistently rated, owned, and addressed.
- Translate risk analysis into clear recommendations and risk-acceptance decisions for senior leadership
JUDGMENT AND DECISION-MAKING:
- Make timely, well-reasoned decisions in ambiguous situations, even when information is incomplete, and clearly communicate the rationale and trade-offs
- Lead internal reviews and investigations, escalate significant matters appropriately, and drive remediation to closure
MONITORING, AUDITING, AND REPORTING:
- Own the enterprise risk-based compliance and privacy auditing and monitoring program, including annual work planning informed by the enterprise risk register, execution, and follow-up, in coordination with Enterprise Risk Management and Internal Audit to avoid duplication and preserve independence
- Oversee hotline and case management, exclusion screening, and corrective action plan tracking through resolution
- Report on all aspects of the Compliance and Privacy programs, including monitoring and audit results, investigations, incidents, and corrective actions
- Establish service level agreements (SLAs) for key compliance and privacy processes and track performance against them
- Develop metrics and dashboards that give leadership meaningful visibility into compliance and privacy health
- Present program results and SLA performance to the Compliance Committee quarterly
- Manage relationships with regulators, external counsel, and auditors as needed
PROJECT AND PROGRAM MANAGEMENT:
- Plan, prioritize, and deliver multiple concurrent compliance and privacy initiatives (e.g., policy overhauls, system implementations, audit remediation, regulatory readiness efforts) on time and within scope
- Set clear milestones, ownership, and status reporting for cross-functional projects
- Apply sound project management practices and tools to coordinate work across a distributed team
QUALIFICATIONS
- Bachelors degree in business or a related field
- 10+ years of professional experience in healthcare compliance, privacy, legal, risk, audit, or a related field
- 5+ years experience building, leading, and coaching teams, including leading managers who in turn lead junior-level staff
- 5+ years of experience and proven ability to build and sustain cross-functional partnerships and influence senior stakeholders, including the ability to explain complex regulatory and privacy topics to non-experts
- Project management experience, evidenced by experience leading and delivering on complex, cross-functional initiatives
- Strong judgment and decisiveness, evidenced by a track record of sound calls under uncertainty and time pressure
- Working knowledge of healthcare regulatory requirements including ERISA, the ACA, the Consolidated Appropriations Act (No Surprises Act, price transparency, MHPAEA), IRS and DOL requirements for HRAs, and state TPA licensing and insurance laws
- Working knowledge of health privacy and security requirements, including HIPAA/HITECH as they apply to business associates, breach notification rules, and state privacy laws
- Experience conducting investigations and performing root cause analysis
PREFERRED
- MBA, JD, or other advanced degree, or certification such as CHC, CHPC, CCEP, CIPP/US, CIPM, CFE, or PMP
- Experience in healthcare or a comparable regulated environment
- Experience leading both compliance and privacy functions, or integrating them under one leader
- Experience scaling a compliance or privacy function in a growing or changing organization
- Familiarity with compliance and privacy technology, analytics, and case management tools
A LITTLE MORE ABOUT US:
- We know healthcare. Our company was founded and is still led by industry veterans who have started and grown several market-leading companies in the space.
- We have raised money from top tier investors who share the same long-term vision as we do of building an industry defining company that will endure over the long run. We are well capitalized.
- Our clients love us. Customer satisfaction rates among employees using Gravie health plans consistently rank above 80% – nearly 40 points above the industry average.
- Our culture is unique. We tend to be non-hierarchical, merit-driven, opinionated but kind people who thrive working in a high-performance, fast-paced environment. People at Gravie care deeply about making a positive impact in the lives of the people we serve.
BENEFITS
Our unique benefits program is the gravy, i.e., the special sauce that sets our compensation package apart. In addition to standard health and wellness benefits, Gravie’s package includes alternative medicine coverage, flexible PTO, up to 16 weeks paid parental leave, paid holidays, a 401k program, transportation perks, education reimbursement, and 2 days of paid paw-ternity leave.
JOB APPLICANTS
If you apply for employment with Gravie, personal information collected via our applicant tracking vendor is subject to our standalone California Job Applicant Notice at Collection, accessible directly within the application workflow and separate from this Policy.
New York
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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