Location: Santa Clara
Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment.
Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done.
About the Role
We are looking for a HR Business Partner (HRBP) to serve as a strategic partner to our Engineering organization. This role sits at the intersection of business strategy and people strategy, working directly with senior engineering leaders (VPs, Directors, and Engineering Managers) to build high-performing teams, shape organizational design, and drive talent, culture, and change initiatives that scale with a fast-moving technology organization. This role requires deep credibility with technical audiences and a strong point of view on what great engineering culture looks like.
What You'll Do
Serve as a trusted strategic advisor to Engineering senior leadership, providing coaching and counsel on organizational design, workforce planning, leadership effectiveness, and team dynamics.
Partner with engineering leaders to translate business and technical roadmaps into people strategies, including org design, span of control, and role architecture as the organization scales.
Lead full-cycle talent management for the client group: performance management, calibration, succession planning, promotion processes, and career development frameworks tailored to engineering career ladders (IC and management tracks).
Use data and analytics (attrition, engagement, hiring velocity, promotion equity, span of control) to diagnose organizational health and recommend proactive interventions.
Partner closely with Talent Acquisition to inform hiring strategy, headcount planning, and workforce composition for engineering.
Lead or co-lead org design and change management efforts tied to reorganizations, M&A integration, or rapid scaling.
Coach engineering managers and directors on leadership skills, difficult conversations, team performance, and conflict resolution.
Drive compensation planning cycles (merit, equity refresh, promotions) in partnership with Total Rewards, ensuring internal equity and market competitiveness for technical roles.
Own employee relations matters within the client group, ensuring fair, consistent, and legally sound resolution of issues.
Champion diversity, equity, and inclusion initiatives specific to the challenges of building diverse technical teams.
Partner cross-functionally (Talent Acquisition, L&D, Legal) to design and deliver programs that meet the unique needs of engineering.
Act as a culture carrier, helping engineering leaders build and reinforce an environment of technical excellence, psychological safety, and inclusion.
What We're Looking For
7–10+ years of progressive HR Business Partner experience, with a significant portion spent directly supporting Engineering, R&D, or other highly technical client groups.
Proven experience operating at a senior level, partnering directly with VP- and Director-level engineering leaders.
Deep understanding of engineering organizational structures, career ladders (IC vs. management tracks), and the specific talent dynamics of technical hiring and retention.
Strong track record leading org design, workforce planning, and change management in a fast-paced, high-growth, or scaling technology environment.
Excellent coaching skills with the credibility and presence to influence senior technical leaders.
Data-driven approach to HR — comfortable building and interpreting people analytics dashboards to inform decisions.
Sound judgment and experience navigating complex employee relations issues; working knowledge of employment law.
Experience leading or contributing to compensation cycles, including equity compensation, for technical roles.
Exceptional communication, influencing, and relationship-building skills across all levels of the organization.
Bachelor's degree required; advanced degree (MBA, HR, Organizational Psychology) or SHRM-SCP/SPHR certification a plus.
The base pay range for this role is between $210,000 and $265,000. Base pay will depend on your skills, qualifications, experience.
This is a regular, in office full-time position with Forward. We are currently in office two days per week (Tuesday/Thursday)
Location : Santa Clara, California
Location: Remote USA
Forward was founded in 2013 by four Stanford Ph.D.s, building the industry's first network digital twin: a mathematically accurate model of the production network. It's the foundation for autonomous networking, giving engineers and AI agents the ability to know the impact of every change before it touches production. That founding instinct still defines how we work. We're accurate and evidence-driven, relentless about clarity, and we'd rather be certain than comfortable, building a groundbreaking platform that transforms how teams run and secure networks across every major cloud and vendor environment.
Global leaders like Goldman Sachs, PayPal, S&P Global, IBM, and Dell trust Forward, alongside fast-growing enterprises and government agencies, realizing an average of $14.2 million in annual benefits, according to IDC. Backed by top-tier investors, including A. Capital, Andreessen Horowitz, Goldman Sachs, MSD Partners, Omega Venture Partners, Section 32, and Threshold Ventures, and headquartered in Santa Clara, we're most proud of our team: curious people who'd rather build what doesn't exist than accept how things have always been done.
About the Role
Forward is looking for a HR Business Partner (HRBP) to serve as a strategic partner
to
our
Sales
organization. This role sits at the intersection of business strategy and people strategy, working directly with senior sales leaders (CRO, VPs of Sales, and Regional/Sales Directors) to build high-performing revenue teams, shape organizational design, and drive talent, culture, and change initiatives that scale with an evolving go-to-market motion. This role requires deep credibility with commercial leaders and fluency in the unique dynamics of a quota-carrying, commission-driven workforce.
What You'll Do
Serve as a trusted strategic advisor to Sales senior leadership, providing coaching and counsel on organizational design, territory/quota structure, workforce planning, and leadership effectiveness.
Partner with sales leaders to translate revenue targets and go-to-market strategy into people strategies, including org design, span of control, and role architecture as the sales org scales or restructures.
Lead full-cycle talent management for the client group: performance management, calibration, succession planning, promotion processes, and career pathing tailored to sales career ladders (RSD/AE, SDR/BDR, sales management, and sales enablement tracks).
Use data and analytics (attrition, ramp time, quota attainment, rep productivity, pipeline health as it relates to headcount, promotion equity) to diagnose organizational health and recommend proactive interventions.
Partner closely with Talent Acquisition on sales-specific hiring strategy, headcount planning, and workforce composition, including seasonal/quarterly hiring cycles tied to sales capacity planning.
Lead or co-lead org design and change management efforts tied to territory realignments, reorganizations, M&A integration, or new market/segment launches.
Coach sales managers and directors on leadership skills, performance conversations, managing underperformance in a quota-driven environment, and team motivation.
Partner with Compensation on commission plan design, quota setting implications, and annual compensation planning cycles (merit, equity, promotions) to ensure competitiveness and pay-for-performance alignment.
Own employee relations matters within the client group, including performance improvement plans and terminations tied to quota non-attainment, ensuring fair, consistent, and legally sound resolution.
Champion diversity, equity, and inclusion initiatives specific to the challenges of building diverse sales teams.
Partner cross-functionally (Talent Acquisition, Legal, Sales Enablement) to design and deliver programs that meet the unique needs of a revenue organization.
Act as a culture carrier, helping sales leaders build and reinforce an environment of high performance, accountability, and inclusion.
What We're Looking For
7–10+ years of progressive HR Business Partner experience, with a significant portion spent directly supporting Sales, Revenue, or other quota-carrying/commission-based client groups.
Proven experience operating at a senior level, partnering directly with CRO, VP, and Director-level sales leaders.
Deep understanding of sales organizational structures, compensation plan design (base/commission/OTE), quota methodology, and the specific talent dynamics of hiring and retaining sales talent.
Strong track record leading org design, workforce planning, and change management in a fast-paced, target-driven, high-growth environment.
Excellent coaching skills with the credibility and presence to influence senior commercial leaders.
Data-driven approach to HR — comfortable building and interpreting people analytics dashboards (attrition, ramp, productivity) to inform decisions.
Sound judgment and experience navigating complex employee relations issues, including performance-based terminations; working knowledge of employment law.
Experience partnering on incentive compensation design and annual compensation planning cycles.
Exceptional communication, influencing, and relationship-building skills across all levels of the organization.
Bachelor's degree required; advanced degree (MBA, HR, Organizational Psychology) or SHRM-SCP/SPHR certification a plus.
The base pay range for this role is between $210,000 and $265,000. Base pay will depend on your skills, qualifications, experience, and location
Location: United States of America
What We Do:
Cybercrime is growing, and more businesses are getting hit by threats that used to target only the biggest organizations. That pushes defenders like us to operate at the highest level, and it deepens our need for good people who want to make a meaningful impact.
Founded in 2015 by former NSA cyber operators, Huntress is a remote-first team working to make enterprise-grade cybersecurity accessible to businesses of all sizes. We work closely with security teams and service providers protecting complex environments, often without the time or headcount to handle it all. That’s why we build our technology in-house and back it with a 24/7 human-led Security Operations Center (SOC). As a result, our platform is never disconnected from the experts who manage it, ensuring our customers' protection.
Huntress now secures more than 6M endpoints and 17M identities worldwide. Those numbers keep growing because more businesses rely on us to help carry the load and operate with more confidence. Every day, you can see that commitment in how we stand with our customers and how we show up for each other.
Reports to: Senior Manager, Community - Field
Location: Remote US
Compensation Range: $94,400 to $118,000 base plus bonus and equity
What You'll Do:
You are the person who brings Huntress to life in the room. You travel to roadshows, tradeshows, and other events, meet people who didn't plan to meet you, and turn genuine conversations into momentum for the business. Give More Than We Take shows up in the way you create value first, listen closely, and build relationships that feel human rather than transactional.
You are Outcome-Obsessed about creating meaningful engagements at events from the moment you leave your house to the moment you return, knowing that booth hours are just the tip of the iceberg. You make sure the right prospects receive thoughtful follow-up, account executives get the context they need, and qualified conversations become fully booked demo opportunities. You take ownership of the details, spot what is missing, and use sound judgment when the process needs to bend to serve the customer and the team.
Responsibilities:
Travel to assigned roadshows, tradeshows, and other events up to 60% of the time
while representing Huntress with energy, professionalism, and a clear understanding of the audience.
Drive meaningful traffic to the Huntress booth with pre-event outreach, and by starting conversations, engaging attendees, and creating reasons for the right people to stop and learn more.
Execute on-site activations and feet-on-the-street account-based marketing activities as directed by your manager.
Build genuine relationships with prospects and partners, in transit, in hallways, over drinks, over dinner, at the booth, at event receptions and parties. Wherever the MSPs are, that’s where you’ll be found.
Drive interest through thoughtful conversation, and book demos at in-person events.
Manage event follow-up and relationship progression so account executives receive timely context, clear next steps, and strong opportunities to pursue.
Use AI tools to research target accounts, prepare for conversations, organize event notes, and draft timely follow-up while applying sound judgment to the final work.
What You Bring to the Team:
Experience engaging prospects at tradeshows, roadshows, conferences, or other in-person events is valuable.
You are curious, self-starting, eager to learn, driven, and comfortable taking initiative without waiting for perfect instructions.
You can engage strangers naturally, make small talk that leads somewhere useful, and build relationships without making the interaction feel transactional.
You are travel-ready and comfortable working in environments that require frequent movement, quick judgment, and consistent energy.
You are detail-oriented and able to follow a process while recognizing when the situation calls for a thoughtful deviation.
You use AI to work faster and smarter in day-to-day preparation, research, and follow-up, with good judgment about accuracy, privacy, and when human context matters most.
What We Offer:
100% remote work environment - since our founding in 2015
Generous paid time off policy, including vacation, sick time, and paid holidays
12 weeks of paid parental leave
Highly competitive and comprehensive medical, dental, and vision benefits plans
401(k) with a 5% contribution regardless of employee contribution
Life and Disability insurance plans
Stock options for
all
full-time employees
One-time $500 reimbursement for building/upgrading home office
Annual allowance for education and professional development assistance
$75 USD/month digital reimbursement
Access to the BetterUp platform for coaching, personal, and professional growth
Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are.
We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status.
We do discriminate against hackers who try to exploit small businesses.
Accommodations:
If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to
accommodations@huntresslabs.com
. Please note that non-accommodation requests to this inbox will not receive a response.
Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our
Candidate Privacy Notice
for more details on our practices and your data privacy rights.
Huntress is committed to creating a culture of inclusivity where every single member of our team is valued, has a voice, and is empowered to come to work every day just as they are.
We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, disability, veteran status, genetic information, marital status, or any other legally protected status.
We do discriminate against hackers who try to exploit businesses of all sizes.
Accommodations:
If you require reasonable accommodation to complete this application, interview, or pre-employment testing or participate in the employee selection process, please direct your inquiries to
accommodations@huntresslabs.com
. Please note that non-accommodation requests to this inbox will not receive a response.
Huntress uses artificial intelligence tools to assist in reviewing and evaluating job applications, including resume screening, skills assessment, and candidate matching and comparisons. These AI tools support our human recruiters in the initial review process, but do not make final hiring decisions without human involvement. By submitting your application, you acknowledge this use of AI in our recruitment process. Please review our
Candidate Privacy Notice
for more details on our practices and your data privacy rights.
#BI-Remote
Location: 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: United States, San Mateo, CA
Why Sony Interactive Entertainment?
Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity.
Senior Director, Strategic Development
Position Overview
Sony Interactive Entertainment is entering an important new chapter in its evolution looking to expand business and identify future growth opportunities. This is a senior leadership position for an individual who combines exceptional strategic judgment with the ability to activate change across complex, highly accomplished organizations. The successful candidate will help SIE move beyond strategy as an annual planning exercise toward a continuous discipline of strategic choices, organizational alignment, experimentation, and measurable business outcomes.
Working directly within the Business Strategy team alongside senior leaders across PlayStation, this individual will build the frameworks, decision mechanisms, and leadership practices that enable executives to own the outcomes of the company's strategic evolution.
The central purpose of this role is not simply to develop strategy. It is to help the organization become better at continuously making, activating, and adapting strategic decisions.
Key Responsibilities
Activate PlayStation's Strategic Transformation
Translate PlayStation's long-range strategic direction into clear, actionable enterprise priorities that connect the company's existing strengths with future growth opportunities.
Help operationalize the strategic shifts defining PlayStation's evolution, including developing new value propositions, driving business model adaptation to new customers and opportunities and moving from periodic planning to continuous strategic adaptation.
Establish practical frameworks that clarify what SIE must preserve, evolve, and newly develop over the next three to five years.
Partner with functional executives to translate enterprise strategy into meaningful choices, commitments, and measurable outcomes within their organizations.
Identify structural, cultural, and operational barriers to transformation and help leadership teams address them.
Activate the strategy by embedding it within cross functional leaders to own it and adapt it as assumptions change.
Establish Continuous Strategic Planning and Adaptation
Build a strategy capability that operates throughout the year, responding to market shifts, emerging technologies, competitive developments, and organizational learning.
Design and implement a continuous strategy operating rhythm, connecting three-to-five-year ambitions with annual priorities, quarterly strategic reviews, and ongoing opportunity assessment.
Develop scenario-planning, strategic sensing, and portfolio-evaluation frameworks that allow leadership to anticipate change rather than simply respond to it.
Connect insights from product, commercial, finance, technology, studios, and external partners into an evolving view of PlayStation's future.
Create the right level of materials for decision-oriented executive forums and then orchestrate those important meetings to find emerging opportunities, challenge assumptions, and recommend adjustments to strategic priorities.
Build mechanisms for leaders to revisit investment assumptions and reallocate attention and resources as evidence changes.
Influence and Mobilize Cross-Functional Executive Leadership
Serve as a trusted strategic partner to senior leaders, bringing together different perspectives and enabling collective decisions on issues that transcend individual business units.
Build trusted relationships with VP- and SVP-level leaders across PlayStation and Sony Group.
Facilitate high-stakes strategic conversations involving competing priorities, resource constraints, and differing perspectives on the future.
Use rigorous analysis (both internal and external), commercial judgment, and compelling narratives to influence decisions without relying on formal authority.
Help executive teams move from conceptual agreement to explicit decisions, accountable ownership, and coordinated action.
Challenge established assumptions constructively while demonstrating respect for the achievements and operational realities of existing businesses.
Identify and resolve strategic misalignment before it becomes an impediment to execution.
Develop the Core / Explore Strategic Framework
Support the development of two distinct but interconnected operating models that allow PlayStation to maximize current business performance while investing in future opportunities.
Establish differentiated frameworks for evaluating core-business optimization and higher-uncertainty exploration initiatives.
Help define how future opportunities are identified, validated, incubated, prioritized, and transitioned into scaled operating businesses.
Partner with Finance and operating leaders to develop portfolio-level investment frameworks that balance near-term returns with longer-term strategic value.
Create transparent decision criteria for advancing, redirecting, or discontinuing strategic initiatives.
Ensure exploration activities are commercially grounded without subjecting early-stage opportunities to inappropriate mature-business performance expectations.
Support leadership in determining where shared capabilities, resources, and partnerships can accelerate both operating systems.
Strengthen Enterprise Strategy Execution and Organizational Capability
Create repeatable approaches that allow SIE leaders to turn strategic direction into coordinated organizational progress.
Develop executive-level strategy activation frameworks, including strategic outcome maps, decision rights, leadership commitments, and progress measures.
Partner with team members to create processes for translating strategic choices into functional priorities without creating unnecessary reporting or bureaucracy.
Facilitate leadership working sessions that resolve trade-offs and create durable ownership of agreed outcomes.
Build strategy toolkits and practical methodologies that functional teams can adopt independently.
Capture and institutionalize lessons from strategic initiatives, including successes, unsuccessful experiments, and changing market assumptions.
Introduce AI-enabled research, synthesis, scenario modeling, and knowledge-management capabilities that increase the speed and quality of strategic work.
Required Experience and Qualifications
The ideal candidate will bring 15+ years of progressive experience in enterprise strategy, business transformation, corporate development, strategic operations, or product leadership, including substantial experience influencing senior executives within complex global organizations.
A proven record of leading enterprise-wide strategic transformation, with tangible examples of changes adopted by business leaders and sustained beyond the initial initiative.
Deep experience influencing cross-functional leadership teams, particularly in situations involving ambiguous authority, competing priorities, and significant organizational complexity.
Demonstrated success designing and implementing strategic planning, portfolio management, or governance frameworks that improved actual business decisions.
Experience in technology platforms, gaming, digital entertainment, consumer ecosystems, or similarly dynamic industries.
Strong commercial and financial judgment, including the ability to evaluate investment trade-offs, growth opportunities, and long-range enterprise value.
Exceptional executive communication, facilitation, and strategic storytelling capabilities.
Experience navigating global organizations and multicultural leadership environments.
Demonstrated ability to use emerging AI and analytical capabilities to improve strategic effectiveness.
At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location.
Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location.
In addition, this role
is eligible
for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products.
This role also may be eligible for a bonus package.
Click
here
to learn more.
The estimated base pay range for this role is listed below.
$275,000
—
$412,400 USD
Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.
Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights.
Equal Opportunity Statement:
Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category.
We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond.
Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.
Location: San Francisco
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: Remote
Workplace: Remote
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: London
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: New York
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the systems that power how we adapt and improve leading open-weight models for legal work.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own the infrastructure behind that effort: distributed training, RL rollout systems, the environments where models learn to use tools and complete complex legal workflows, and the internal systems the team uses to manage data, run evals, and launch and track training jobs. You’ll help decide what we build, what we adopt, and how the pieces fit together. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the stack.
We’re looking for research engineers who have built demanding ML or distributed systems, can debug across the stack, and want to work closely with researchers to make training faster, more reliable, and easier to iterate on.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Scale our post-training stack, supporting SFT and RL on leading open-weight models.
- Build distributed rollout infrastructure that coordinates model inference, tool execution, and collection of training experience for long-horizon tasks.
- Build the infrastructure for reproducible agent environments where models can interact with documents, tools, and external systems during training and evaluation.
- Own the performance and reliability of training runs, including GPU utilization, checkpointing, failure recovery, and observability.
- Identify and remove bottlenecks across training and inference to shorten the path from research idea to useful result.
- Build the internal tools and services the team runs on: training data management and versioning, running evals and browsing results, and launching and tracking training jobs and experiments.
- Integrate models into production, including serving, latency, cost, and online evaluation, so research reaches customers quickly and safely.
- Partner closely with researchers to turn experimental workflows into dependable systems while keeping room for rapid experimentation.
WHAT YOU HAVE
- Experience building ML infrastructure, distributed systems, or research tooling, with ownership of performance, reliability, and operation.
- Strong Python and generalist software engineering skills across backend services, data systems, and internal tools, with familiarity with PyTorch, JAX, or similar ML frameworks.
- Experience with distributed training or inference, including diagnosing performance bottlenecks and failures across the stack.
- Understanding of post-training workflows; experience with RL rollouts, agent environments, or sandboxed tool execution is a plus.
- Practical judgment about what to build versus adopt, and the ability to partner with researchers and ship quickly as needs evolve.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: San Francisco
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: London
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: Remote
Workplace: Remote
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: New York
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
In this role, you'll build the data and measurement systems that power our post-training, benchmarking, and agent capability efforts.
We recently post-trained our first model built for legal work, and we’re now building the team to scale up our post-training efforts. You’ll own synthetic data pipelines, evaluation design, the tasks and grading behind training environments, and the systems that turn feedback from domain experts into training signals and rewards. These are tasks where correctness often can’t be verified automatically, so defining and measuring quality is a core research challenge. You’ll join a small, high-bar team of hands-on engineers and researchers, where each person owns a large part of the work.
We’re looking for research engineers who can build reliable data and evaluation systems, question what a metric actually tells us, and work closely with researchers and legal experts to turn model failures into measurable improvements.
Learn more about our work at harvey.ai/research http://harvey.ai/research.
WHAT YOU'LL DO
- Build synthetic data pipelines that generate, filter, and curate training and evaluation samples for complex legal reasoning and agentic workflows.
- Design evaluations and verifiers that reflect real legal work, calibrate them against expert judgment, and investigate where they fail.
- Build and maintain capability benchmarks like our Legal Agent Benchmark (LAB), along with product-focused evals that track how models perform on real customer workflows.
- Work with legal domain experts to define quality metrics, rubrics, and other grading mechanisms for training and evaluation.
- Own training and evaluation data quality, including provenance, coverage, and safeguards against contamination.
- Close the loop from product usage and customer feedback to new evaluations and training data, so models improve where customers need them most.
- Partner with researchers to investigate model failures, distinguish real gains from misleading metrics, and use findings to guide training and release decisions.
WHAT YOU HAVE
- Experience building data pipelines, ML evaluation systems, or experimentation tooling, with strong Python skills and ownership of production-quality code.
- A rigorous approach to measurement, including statistical reasoning, experimental design, and understanding when a metric can mislead.
- The ability to translate ambiguous goals or expert judgment into structured datasets, rubrics, and measurable criteria.
- Experience with synthetic data, LLM evaluations, automated raters, or preference data is a plus. Strong data and measurement engineering experience close to ML model development is valuable even without prior LLM work.
We are hiring for this role across multiple levels.
COMPENSATION
$230,000 - $450,000 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-DZ1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: 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.
УдалённоRemote USA
United States of America
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
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