Location: San Francisco, CA | New York City, NY | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint: the sites, the hardware inside them, and the supply chain that delivers it. The Security Fusion Platform is where physical security signals from across that footprint are correlated and put in front of the analysts who act on them. It carries continuous monitoring, audit evidence, metrics, and analyst response, along with the classification and analytics pipelines that turn sensor data into events. You'll build and own the platform analysts work from.
This is a foundational role. You'll build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production. The sensors and systems at each site belong to other DCSE engineers; you define the event contract their owners deliver to, and you build the classification and analytics pipelines that run over what those sources produce. Physical security systems engineers own the operations spaces; you own the software that runs in them. You'll work alongside engineers focused on the sites themselves. What you lead, you own end to end: the design, the technical approach, and the result in production.
You'll work with external vendors and integrators, setting requirements and acceptance criteria for what you own and deciding what the team builds itself. We use Claude throughout our engineering workflow and expect you to as well.
This role involves regular travel to data center sites. No security clearance is required. These are critical services, and you'll take part in on-call for them.
Key responsibilities
Design and build the event bus and normalized event schema:
source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed
Build correlation and alerting:
the rules and services that turn events from independent sources into alerts an analyst can act on
Build the classification and analytics pipelines:
computer vision and multi-sensor fusion, with results landing on the event bus
Build analyst surfaces:
the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events
Deliver audit evidence:
durable, tamper-evident event history, evidence exports, and the retention and access controls around them
Instrument metrics and self-monitoring:
detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule
Deploy across sites:
site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts
Specify the compute the platform runs on
(servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline
Write requirements and acceptance criteria
for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work
Minimum qualifications
Have built and run event-driven backend systems in production
Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka
Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production
Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor
Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted
Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it
Build tools for people who use them under pressure and iterate with those operators
Preferred qualifications
Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one)
Experience building ML or computer vision inference pipelines over video and sensor streams
PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data
Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody
Experience using AI-assisted development tooling as a core part of your workflow
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$405,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
seniorSan Francisco, CA | New York City, NY | Seattle, WA
Location: New York, NY, United States
About Us
Fanatics is a leading global sports platform redefining how fans connect with the teams, players and moments they love. Our businesses — Fanatics Commerce, Fanatics Collectibles, Fanatics Betting & Gaming, Fanatics Events, Fanatics Advertising, Fanatics Markets and Fanatics Studios — maximize the presence and reach for hundreds of partners globally and create a one-stop experience that allows fans to buy, bet, collect, and earn, while engaging with sports in deeper, more immersive ways. This includes licensed fan gear and lifestyle products, sportsbook and iGaming, physical and digital trading cards, live events, premium sports entertainment content, credit card offerings and more. Together, they form a powerful, integrated ecosystem — connected by the Fanatics ONE loyalty program and FanCash, the currency of sport — delivering personalized experiences to over 100 million fans worldwide. Fanatics holds partnerships with over 900 sports properties, from professional leagues and players’ associations to teams, colleges and retail partners; over 7,000 athletes and celebrities; and over 2,000 retail locations, including all Lids stores. Backed by a team of more than 22,000 employees, Fanatics is committed to relentlessly enhancing the fan experience.
Job Summary
Fanatics Betting & Gaming (FBG) is building the industry's most trusted, scalable, and fan-centric sportsbook experience. Our Internal Platforms power critical systems that support customer operations, marketing, support, risk, and data—through a combination of Java backend services, APIs, event-driven systems, and integrations with the SaaS and CRM platforms our business teams run on.
We are seeking a
Staff Java Software Engineer
to set technical direction for the services and integrations that Internal Platforms runs on. This is a senior individual contributor role for an engineer who operates with minimal guidance, takes on our most complex and often cross-functional problems, and raises the bar for everyone around them.
At this level, your impact is measured beyond the code you write. You will own architecture for significant parts of the platform, drive decisions that span multiple teams and systems, mentor other engineers, and partner directly with Product, Operations, Support, Marketing, Risk, and Data leadership to shape what gets built and why. You will still be hands-on—Staff engineers at FBG write and review code every week—but you will spend meaningful time on design, technical strategy, and multiplying the output of the teams you work with.
You do not need to be a Salesforce specialist. Some of our systems integrate with Salesforce for CRM and workflow automation, so exposure to it is a nice to have—but we're hiring for strength in Java, distributed systems, and integration design, and we expect you to pick up the platform specifics on the job.
Key Responsibilities
Technical Leadership & Architecture (Primary Focus)
Own the architecture for major services, integrations, and data flows within Internal Platforms, from problem definition through production operation.
Lead design for complex, often cross-functional initiatives—defining the approach, surfacing trade-offs, and driving alignment across engineering teams and stakeholders.
Break ambiguous, department-level problems into clear technical plans and workstreams that other engineers can execute against.
Evaluate and select technologies, patterns, and vendors; know when a sophisticated design approach is warranted and when the simpler answer is the right one.
Establish and evolve engineering standards for the team—API design, testing strategy, observability, deployment, and integration patterns—and get them adopted in practice, not just documented.
Identify systemic technical debt and reliability risk across the platform, build the case for addressing it, and sequence the work alongside feature delivery.
Hands-On Engineering
Design, build, and maintain Java-based backend services (Spring Boot or similar frameworks) that are scalable, resilient, and well-tested.
Take on the hardest technical problems on the team: high-throughput event processing, complex multi-system integrations, thorny data integrity issues, and production incidents that cross service boundaries.
Diagnose problems at the root cause rather than the symptom, and translate what you learn into durable fixes and better instrumentation.
Set the quality bar through your own code and through high-signal code reviews that teach as well as gate.
Contribute to internal web applications and user interfaces backed by Java services where it moves the work forward.
Mentorship & Force Multiplication
Mentor and coach Senior and mid-level engineers through design review, pairing, and direct feedback; help them grow the judgment to handle complexity independently.
Create learning and growth opportunities for teammates—delegate meaningful design work, sponsor stretch assignments, and share context generously.
Onboard and ramp new engineers into the platform's systems and conventions.
Write the documentation, runbooks, and design records that let the team operate and extend the platform without you in the room.
Model an inclusive, collaborative environment where opposing views are actively invited and disagreement is resolved on the technical merits.
Cross-Functional Partnership & Delivery
Partner with Product Managers, Technical Program Managers, and business stakeholders to shape roadmaps—bringing technical feasibility, sequencing, and risk into the conversation early rather than reacting to finished requirements.
Work directly with Marketing, Operations, Support, Risk, Compliance, and Data teams to ensure platform capabilities meet business needs and regulatory obligations across jurisdictions.
Represent Internal Platforms in architecture and design discussions with other engineering teams, negotiating clean contracts and shared ownership boundaries.
Communicate complex technical problems, trade-offs, and decisions clearly to both engineering and non-engineering audiences, including leadership.
Drive predictable delivery for initiatives you own: scope, estimate, unblock, and own the outcome—including the parts that depend on other teams.
Engage external partners and vendors on integration design and technical escalations where needed.
Third-Party & SaaS Platform Integration
Own the integration architecture between our Java services and the third-party platforms our business teams depend on—REST APIs, platform events, middleware—including data ownership, consistency, and failure handling.
Define scalable, reusable integration patterns and prevent the platform sprawl that comes from point-to-point fixes.
Lead resolution of complex integration issues spanning backend services, vendor platforms, and data pipelines.
Partner with platform-specialist engineers (including our Salesforce-focused engineers) to keep integration boundaries clean and maintainable.
Operational Excellence
Own production health for the services in your remit: SLOs, alerting, on-call quality, incident response, and post-incident follow-through.
Anticipate failure modes, capacity limits, and blockers before they surface, and build the safeguards in advance.
Improve engineering practice across the team—CI/CD, test automation, release safety, and developer productivity.
Hold the line on the standards required of a regulated, highly available gaming platform.
Qualifications
Required
8+ years of professional software engineering experience, with deep expertise in Java.
Demonstrated ownership of the architecture and delivery of complex production systems, including work that spanned multiple teams or functions.
Strong experience designing APIs and integrating distributed systems, with sound judgment about consistency, failure handling, and service boundaries.
Track record of operating with minimal guidance: taking an ambiguous problem, defining the approach, and driving it to production.
Experience mentoring engineers and raising technical standards on a team—through design review, code review, and direct coaching.
Ability to communicate complex technical concepts and trade-offs clearly in writing and in person, to technical and non-technical audiences alike.
Experience with Git-based workflows, code reviews, and CI/CD pipelines.
Experience operating services in production, including on-call ownership and incident response.
Preferred
Experience with event-driven architectures (Kafka or similar) at meaningful scale.
Experience in cloud environments (AWS preferred), including infrastructure-as-code.
Experience with highly available or regulated systems (gaming, fintech, payments).
Experience contributing to internal web UIs or tooling, including Java-backed web frameworks and/or modern front-end frameworks consuming Java APIs (React, Angular, etc.)
Experience working with AI model or agent platforms, including building on or integrating agents into production workflows. Familiarity with platforms such as Anthropic, OpenAI, Amazon Bedrock, LangChain, Google Vertex AI, Microsoft Copilot Studio, CrewAI, or AutoGen is a plus.
Fluency with AI-powered coding assistants to design, build, and test new functionality from the ground up—moving quickly while maintaining high code quality and test coverage—and interest in helping the broader team adopt these workflows effectively.
Nice to Have
Exposure to Salesforce as an integration target or platform—Salesforce APIs, platform events, or light development work in Apex, Lightning Web Components, or Flows. Helpful context, not a requirement.
Salesforce certifications (Administrator, Developer).
What We Value
Passion for building high-quality internal platforms that directly impact business outcomes.
Strong ownership mindset: you own the outcome, not just your piece of it.
A solutions-first approach—you anticipate problems and bring options, not just escalations.
Genuine interest in making other engineers better.
Comfort operating in a fast-paced, evolving environment with incomplete information.
Ranges will change based on country and state of residence, which are reflected in Geographical Zones defined by Fanatics Betting and Gaming. The range incorporates all of our Geographical Compensation Zones and is subject to change as the Zone associated with the actual offer is confirmed. In addition to the base and bonus, full-time employment, and more. For information about our benefits, please visit
https://benefitsatfanatics.com/
Salary Range
$1
—
$1 USD
By submitting your application, you agree to our terms of service and acknowledge you have read our
Candidate Privacy Policy.
Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it
here
.
Location: Russia; Moscow; Perm
Workplace: remote
About Xsolla
Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.
For more information, visit xsolla.com.
About the Role
We are hiring a Staff Software Engineer to own the smart wallet and account abstraction layer of XsollaZK, Xsolla's Web3 platform on a zkSync-based L2. This is an individual contributor role with a large technical scope. You are the technical anchor for how millions of players get an on-chain account they never have to think about.
The product. Every player who signs in with Xsolla ID receives a deterministic, non-custodial smart account. The account is derived from their identity claim, is identical on every device, and its private keys never leave the client. It is not a separate wallet screen: it is the player's inventory. It backs:
minting and gifting;
trading on our Bazaar marketplace;
Merkle-based reward airdrops;
gas sponsorship;
an in-app dApp browser that exposes the same signer to third-party applications through an EIP-1193 provider.
Responsibilities
The technical strategy and architecture of the smart wallet platform: account model, signing, session management and gas abstraction at scale
The smart account and permissioning model, evolved to meet both product and compliance needs
The security model where our signer meets third-party applications: what a player is actually approving, and proof that the UI shows it
The custody and recovery roadmap, from today's interim mechanisms (including raw key export) to
MPC
-based custody
Cross-team technical decisions on account architecture, SDK contracts, data modeling and platform reliability, with buy-in from the wallet, marketplace, SDK, mobile and security teams
Engineering standards in the Web3 domain
Production escalations in the wallet and account abstraction domain
WHAT YOU WILL DO
Design and evolve the
ERC
-4337 user operation lifecycle (prepare → sign → submit → confirm),
EIP
-7702 delegation, deterministic address derivation from identity, and the session-key and permission primitives (including origin-bound Smart Sessions) that let players act without a prompt on every transaction
Set the paymaster and gas-sponsorship strategy: what we sponsor, how we meter and cap it, how we defend it from abuse, and how it degrades when sponsorship is unavailable
Define
EIP
-1193 /
EIP
-6963 provider behavior, origin-bound and policy-versioned sessions, trust tiers, and the transaction and signature confirmation flow
Design recovery paths (passkeys, guardians, social recovery) that a non-crypto-native player can complete without losing assets
Identify systemic risks (key management, signature phishing, reorgs and indexer staleness, bundler and
RPC
dependencies, contract upgrade paths) and lead initiatives that resolve them before they become incidents
Write RFCs and design docs; review critical code, contracts and designs
Work with product, security, legal and infra teams to align on the roadmap and turn business and regulatory needs into well-scoped technical plans
Create leverage for the engineering org through documentation, tooling and mentorship
Serve as the escalation point for complex production issues: a stuck user operation, a drained paymaster, a signing prompt a player didn't understand
Set up and maintain AI tooling in the repositories (Claude Code, Codex, Cursor: rules, context, harness) so the team uses it effectively
REQUIRED
Experience
8+ years of engineering in the Ethereum ecosystem working with crypto wallets and smart wallets
Designing or operating a production smart wallet or account abstraction system serving real users and real value
Shipping and operating systems where a bug meant lost funds. You can talk concretely about the guardrails, reviews and rollback paths you put in place
Account abstraction and smart wallets
ERC
-4337 in depth: EntryPoint (v0.6 through v0.8), the UserOperation lifecycle, bundler and paymaster roles, validation rules (
ERC
-7562), gas estimation and its failure modes, counterfactual deployment, signature validation for undeployed accounts (
ERC
-6492)
EIP
-7702 and the post-Pectra landscape:
EOA
delegation, its interaction with EntryPoint v0.8, and the risks it introduces (residual key authority, delegation phishing, storage collisions)
Building on or extending production smart account implementations; modular account standards (
ERC
-7579 /
ERC
-6900)
Session keys and delegated permissions: scoped, time-limited, policy-bound authority; TTLs and contract allowlists, origin binding, permission revocation;
ERC
-7710 /
ERC
-7715
Signature schemes and wallet interfaces:
EIP
-712 typed data,
ERC
-1271 contract signatures, WebAuthn / passkey (P-256) signers;
EIP
-1193,
EIP
-6963,
EIP
-5792 batched calls,
ERC
-7677 paymaster interfaces
Smart contracts and
EVM
Solidity and the
EVM
: reading, reviewing and writing account, paymaster and module contracts; gas-aware design; upgradeability and migration patterns; working effectively with external auditors
L2 specifics and their effect on wallet design: native account abstraction on zkSync-family chains, transaction and fee models, finality and reorg behavior,
RPC
and indexer semantics
Backend
Go: idiomatic code, concurrency patterns, performance profiling
TypeScript and SDK design: client-side SDK surfaces that internal and external teams build on
Distributed systems and their trade-offs (consistency, availability, failure modes); reconciling off-chain state against an authoritative on-chain result
Data and infrastructure
PostgreSQL: schema design, query optimization, migrations at scale
Kubernetes: deploying, operating and debugging services
Asynchronous messaging and event-driven design (Kafka or
NATS
): consumer groups, at-least-once delivery
Git, CI/CD
Security
Key management in production: platform secure storage (Keychain / Keystore), HSMs,
MPC
or threshold signing, and the operational discipline around each
Wallet threat modeling: signature and delegation phishing, malicious dApp origins, replay and cross-chain replay, token approval abuse, paymaster griefing and
DoS
Leadership
Leading multi-quarter technical initiatives across teams
Influencing architecture and standards beyond your immediate team
RFCs and design docs that stand on their own and are actionable without you in the room
AI-assisted engineering
Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for development and review, including configuring them for a repository
English
English at C1 level
Nice to Have
Hands-on experience with
ZK
Stack and
zk
-rollups
Hands-on experience with embedded and ecosystem wallet and
AA
infrastructure technologies (thirdweb, Privy, Dynamic, Turnkey, Pimlico, Alchemy, Biconomy, ZeroDev, Safe{Core}), with clear views on build versus buy
MPC
/ threshold custody, social recovery or guardian-based recovery in a consumer product
NFT
and token infrastructure at scale:
ERC
-721 /
ERC
-1155 /
ERC
-20 mechanics, marketplace contracts, Merkle-based airdrop and claim distribution, chain indexing services
Contributions to open-source wallet, security or identity projects, including authoring or reviewing
ERC
/
EIP
standards
Compliance requirements for crypto consumer products:
KYC
/
AML
, geofencing,
MiCA
, SOC 2, ISO 27001,
GDPR
data minimization, audit logging
Identity and auth integration for wallet derivation: OAuth 2.0 /
OIDC
, JWT verification, token scoping
Platform or infrastructure engineering: building systems other engineers build on
Owning a mobile wallet surface: React Native / Expo, WebView provider injection, native signing UI
Gaming industry experience: platforms for game developers, publishers or players
How We Work
Decisions in writing. Significant technical decisions are written up as an RFC or ADR that lays out the options and trade-offs. We work across time zones, so a design has to stand on its own.
AI is part of everyday engineering. We use AI coding tools for development and review, and we treat configuring them for a codebase as real engineering work.
HOW WE HIRE
Intro call. Your background, your motivation and the role.
Technical interview. Built directly on the What you will own and Required sections above. We won't ask about anything this posting doesn't promise.
System design. You design part of a wallet or account abstraction platform end to end and walk us through the trade-offs.
Bar raiser. An engineer from outside the hiring team checks that you raise the overall engineering bar.
Benefits
We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play.
EMPLOYMENT DETAILS
Location: Remote
Employment Type: Full-time
Schedule: 10:00–19:00 (flexible)
Задачи:
— Поддерживать продуктовые чарты для платформенных продуктов, включая пользователей, проблемные области, нецелевые задачи и метрики успеха
— Определять и владеть видением, дорожной картой и OKR для основных возможностей платформы
— Выявлять и приоритизировать болевые точки разработчиков, используя качественные и количественные данные с фокусом на влияние
— Переводить потребности платформы в четкие продуктовые требования и приоритеты
— Сотрудничать с инженерной командой для оценки технических компромиссов и решений, ориентируясь на масштабируемые возможности платформы, а не на индивидуальные решения для команд
— Продвигать стандарты платформы среди команд
— Определять и отслеживать метрики успеха, такие как производительность разработчиков, надежность и эффективность затрат
— Согласовывать инвестиции в платформу с целями роста и масштабирования компании
— Проводить исследование через интервью с разработчиками, опросы Dev Experience, анализ прерываний поддержки, обзоры инцидентов и метрики платформы (например, DORA, надежность CI/CD)
— Руководить миграциями и устареваниями с эмпатией, ясностью и последовательностью
— Тесно сотрудничать с EM и старшими инженерами, проводя большую часть времени встраиваясь в инженерные команды
Требования:
— Сильное продуктовое мышление в сочетании с технической грамотностью в области разработки ПО, инструментов для разработчиков или систем
— Опыт работы с высокотехническими внутренними продуктами (платформы, инструменты, инфраструктура или системы для разработчиков)
— Способность эффективно работать в условиях неопределенности и конфликтующих приоритетов
— Доказанная способность оспаривать приоритеты и добиваться согласия среди внутренних заинтересованных сторон
— Склонность к использованию рычагов, стандартов и умолчаний, основанная на убеждении, что стандартизация раскрывает креативность
— Твердое концептуальное понимание/знакомство с облачными платформами и инфраструктурой, современными распределенными системами, компромиссами между надежностью и скоростью, абстракцией и гибкостью, стандартизацией и автономией команд, SLO, метриками DORA и метриками эффективности затрат
— Способность анализировать и оспаривать технические RFC и архитектурные предложения на концептуальном уровне, ориентированном на результат
Преимущества:
— Предыдущий практический опыт работы инженером-программистом или менеджером инженерной команды перед переходом в продуктовый менеджмент
Условия:
— Помощь с релокацией в Испанию (Барселона)
— Конкурентный финансовый пакет с акциями, отпуском и медицинской страховкой
— Ежемесячный щедрый бюджет на уроки на Preply.com, бюджет на обучение и время для саморазвития
— Доступ к бесплатным платформам поддержки психического здоровья
— Доступ к wellness- и фитнес-центрам, партнерским с Gympass по всей Испании
Описание команды:
Платформенный триб в Preply объединяет команды, отвечающие за внутренние основы, которые позволяют инженерам надежно и масштабируемо строить, развертывать и эксплуатировать Preply. В настоящее время в Preply около 200 инженеров, с планами увеличить команду еще на 100 в этом году, что делает платформенный триб критически важным для следующей фазы роста компании.
Location: San Francisco
APPLICATIONS CLOSED
The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers!
Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research.
NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention.
FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS
Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech
Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn
Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago
UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin
UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale
FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS
McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo
EARLY CAREER TALENT @ PERPLEXITY
Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around:
- Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school.
- Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered.
- Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members.
- Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role.
- Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission.
ACADEMIC REQUIREMENTS
If you're not applying from a focus school listed above, we typically require you to possess the following qualifications:
1. GPA of ≥3.92, averaged across all CS and Math classes; and
2. Grade of A or A+ in your school's upper-level algorithms course.
Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.
NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY
While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form.
NOTE ON FELLOWSHIP OPPORTUNITIES
This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.
Location: San Francisco
APPLICATIONS CLOSED
The general application portal has closed for 2026. We will reopen applications at some point in 2027. Thank you for your interest in Perplexity careers!
Welcome! This is the general application portal for university students and recent graduates who wish to be considered for full-time Member of Technical Staff positions at Perplexity. Our elite new grad cohorts enjoy unparalleled mentorship, top-of-market compensation, and the chance to tackle some of the deepest, thorniest challenges in frontier intelligence https://www.perplexity.ai/hub/blog/category/research.
NOTE: if you attend one of our focus schools listed below, please do not apply via this portal as it is infrequently monitored due to high volume. Apply instead via the school-specific application portal below to ensure your application receives priority attention.
FOCUS SCHOOLS (UNITED STATES) - APPLICATION PORTALS
Caltech https://pplx.ai/2026Caltech | Columbia https://pplx.ai/2026Columbia | Cornell https://pplx.ai/2026Cornell | CMU https://pplx.ai/2026CMU | Duke https://pplx.ai/2026Duke | Georgia Tech https://pplx.ai/2026GATech
Harvard https://pplx.ai/2026Harvard | MIT https://pplx.ai/2026MIT | Michigan https://pplx.ai/2026Michigan | Northwestern https://pplx.ai/2026Northwestern | NYU https://pplx.ai/2026NYU | Penn https://pplx.ai/2026Penn
Princeton https://pplx.ai/2026Princeton | Purdue https://pplx.ai/2026Purdue | Stanford https://pplx.ai/2026Stanford | UC Berkeley https://pplx.ai/2026Berkeley | UChicago https://pplx.ai/2026UChicago
UCLA https://pplx.ai/2026UCLA | UIUC https://pplx.ai/2026UIUC | UNC Chapel Hill https://pplx.ai/2026UNC | UT Austin https://pplx.ai/2026UTAustin
UWashington https://pplx.ai/2026UW | Yale https://pplx.ai/2026Yale
FOCUS SCHOOLS (CANADA) - APPLICATION PORTALS
McGill https://pplx.ai/2026McGill | UBC https://pplx.ai/2026UBC | UToronto https://pplx.ai/2026UToronto | Waterloo https://pplx.ai/2026Waterloo
EARLY CAREER TALENT @ PERPLEXITY
Perplexity believes that exceptionally talented individuals at any stage can thrive in our high-velocity, high-ownership culture. Our early career talent program revolves around:
- Breadth: New grads at Perplexity work across the stack, from Perplexity's agent harnesses to our AI inference and training systems. Many of our most beloved features and most important systems were shipped by individuals fresh out of school.
- Depth: New grads are entrusted (and expected) to dive deep into whatever problem domains you work on. Often, your work will require you to become a world expert in some problem space that few others in the world have encountered.
- Mentorship & Growth: We keep the size of our entering new grad cohorts at well below 10% of our technical team. Each individual enjoys a rich network of mentors to help them grow, and our new grads have a track record of becoming some of Perplexity's most senior and prolific team members.
- Recognition: We select for the best and we recognize them accordingly. We set our early career compensation to rise well above that of top tech companies and startups. Post-hire, we aggressively recognize and reward growth in role.
- Mission: Perplexity is AI for people who expect more. Our mission is to build frontier intelligence for the world's most discerning users, and each contribution you make will directly advance that mission.
ACADEMIC REQUIREMENTS
If you're not applying from a focus school listed above, we typically require you to possess the following qualifications:
1. GPA of ≥3.92, averaged across all CS and Math classes; and
2. Grade of A or A+ in your school's upper-level algorithms course.
Additional advanced coursework in areas such as systems, AI/ML, advanced math, and other rigorous subjects is highly welcome.
NON-QUALIFYING APPLICATIONS - EVIDENCE OF EXCEPTIONAL ABILITY
While you're welcome to submit your application if you don't meet these criteria, we will be looking for other evidence of exceptional ability. You are encouraged to briefly describe this evidence in response to the "Anything Else" question at the bottom of the application form.
NOTE ON FELLOWSHIP OPPORTUNITIES
This portal accepts applications for full-time roles at Perplexity. Internship applications are not accepted via this portal. If you're interested in short-term opportunities with our team, you may instead be interested in the Perplexity Research Fellowship. The Fellowship has a separate application process detailed here https://pplx.ai/fellowship. Note that Fellowship applications are extremely competitive; in particular, we don't expect to admit any undergraduate students to the Fellowship before their final year of study.
Location: United States (Remote); Seattle, Washington
Workplace: Remote
ROLE SUMMARY
We’re hiring a Staff Software Engineer to join the Replication Foundations team within Temporal’s Cloud Global Services (CGS) organization.
Replication Foundations owns and evolves Temporal’s core replication stack in Temporal OSS—the distributed systems backbone behind key Temporal Cloud capabilities such as High Availability namespaces, cross-cluster and cross-region failover, and migration products that enable customers to move workloads between self-hosted Temporal and Temporal Cloud. The team also builds foundational scalability and reliability mechanisms that support Temporal at scale.
In this role, you’ll help set the technical direction for Temporal’s distributed replication systems. You’ll lead complex, correctness-critical initiatives spanning architecture, design, implementation, rollout, and operations. You’ll work across teams to evolve reliable and scalable replication capabilities that support both the open source project and Temporal Cloud.
WHAT YOU'LL DO
- Set the technical direction and evolve the architecture of Temporal’s OSS replication stack, from problem definition through rollout and operational support.
- Lead the design and implementation of replication protocols that power:
- High Availability namespaces
- Cross-cluster and cross-region replication
- Migration between Temporal clusters, including cloud-to-self-hosted and cloud-to-cloud scenarios
- Drive scalability and reliability initiatives such as:
- Multi-cell namespaces
- Enabling a namespace to span multiple clusters
- Improving load distribution and handling hot spots
- Define and communicate system-level guarantees, including consistency models, ordering, idempotency, failure recovery, performance, and operational behavior.
- Identify architectural risks and opportunities, and shape the technical roadmap for replication capabilities that support current and future cloud products.
- Partner with Cloud Enablement, CGS, Product, and other engineering teams to align OSS replication foundations with customer and product needs.
- Lead design reviews, raise the quality of implementation and testing practices, mentor engineers, and provide technical guidance across the organization.
- Lead or contribute to debugging complex production issues, incident response, and follow-up improvements related to replication and core system behavior.
WHAT YOU'LL BRING
- A track record of designing and delivering complex production distributed systems, including systems where correctness, availability, and performance are critical.
- Deep understanding of distributed systems fundamentals such as replication, partitioning, consistency, fault tolerance, durability, concurrency, and failure recovery.
- Experience defining system architecture, protocol behavior, invariants, and trade-offs in ambiguous or evolving problem spaces.
- Experience debugging complex production issues, including concurrency bugs, data inconsistencies, partial failures, and performance bottlenecks.
- Proficiency writing production-quality concurrent code in Go; experience with Java, C++, or similar systems languages is also welcome.
- Strong written and verbal communication skills, including the ability to explain complex designs and trade-offs to both technical and cross-functional audiences.
- Demonstrated ability to influence technical direction across teams, build alignment without direct authority, and mentor engineers.
- A thoughtful and curious approach to understanding how systems behave under load, failure, and changing workload conditions.
NICE TO HAVE
- Experience designing or maintaining replication protocols or data-plane infrastructure.
- Experience with multi-cluster or multi-region architectures, including active-active or active-passive systems.
- Familiarity with database internals, log-based replication, or event-sourced systems.
- Prior contributions to large open source projects or distributed systems infrastructure.
Temporal Technologies is an Equal Opportunity Employer. Temporal Technologies does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need. We embrace and celebrate differences and diversity.
Temporal is committed to providing access, equal opportunity, and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. If you need to request a reasonable accommodation, please let your Recruiter know so we can assist.
Location: British Columbia
Workplace: Hybrid
Safe Software is looking for an experienced developer to join our Cloud Applications team and take a leading technical role in our FME AI Service, AI Assist Plugin, and future AI product offerings.
This is deliberately a hybrid role. We need the software engineering depth to build and operate production services, alongside the experimental instinct to determine empirically what makes an LLM-based agentic system work. Many of the problems don't have standard solutions yet, so you'll be the person who designs the experiment, measures the result, and turns the finding into a shipped improvement. We have an immediate opening and are excited to find the right candidate to join our team.
ABOUT THE TEAM
As a member of our Cloud Applications development team, you will take technical leadership of designing and developing new features, as well as maintaining existing functionalities in our products. You will primarily work in Python (FastAPI and LangChain), with a willingness to learn new languages and technologies as needed. You will also contribute to support our live applications.
The team practices agile development and utilizes Kanban boards to manage their backlog, epics and stories. As a Staff Software Developer - AI Products, you will regularly participate in team meetings (stand-ups, planning), lead technical decision-making processes, and work closely with our Product Managers, UX Designers, and QA, as well as Customer Experience team members who review live traces from AI applications.
WHAT YOU’LL BE DOING
As a Staff AI Developer, you will:
- Design and build server-side services and APIs (FastAPI).
- Design and build modular agentic workflows to augment the FME platform capabilities.
- Stay up to speed with developments in AI and LLM tooling, and incorporate relevant ideas into our products.
- Participate in every aspect of the development cycle, including shaping specifications with the product owner, developing clean and maintainable code, writing unit and integration tests, doing code reviews, and maintaining and improving existing code.
- Collaborate, support, and share expertise with other team members.
- Work closely with the product owner and design team to deliver a high quality and consistent user experience.
- Maintain and continuously improve the building and delivery of our AI service to reduce query latency and improve assistant response quality.
- Investigate, evaluate the impact, and resolve anomalies and bugs in live applications.
- Participate in the team’s light on-call rotation to support live applications.
QUALIFICATIONS, SKILLS, AND COMPETENCIES
Safers come from a variety of backgrounds with a diversity in skills and knowledge. That said, we find that those who are most successful in this role have experience with the following areas.
Background
- Bachelor's degree in Computer Science or a related field, or equivalent experience.
- Typically, at least 7 years of experience working on production backend systems.
- A track record of leading technically ambiguous projects and raising the capability of the engineers around you.
Technical skills
- Project or work experience with agentic LLM-based applications, including techniques such as RAG, prompt and context engineering, and tool calling.
- Demonstrated experience evaluating LLM systems: building eval sets, defining quality metrics, and tracing and debugging non-deterministic behaviour.
- Depth in at least one modern backend language, and the ability to pick up others as the work demands.
- Experience with a modern backend web framework such as FastAPI.
How you Work
- An empirical mindset — comfort designing and running experiments to reach a decision, rather than reasoning about which approach should be best.
- Strong interest in the craft, a curious mind, and eagerness to learn new tools and technologies.
- Able to explain technical tradeoffs clearly to teammates and stakeholders.
- Excellent organizational skills, with the judgment to prioritize your own work efficiently.
- Resourcefulness and the ability to work well in a team-based environment.
DESIRED SKILLS / BONUS POINTS
We don't expect any single candidate to have all of these.
Evaluation and experimentation:
- Familiarity with LLM evaluation libraries such as Ragas, DeepEval, openevals, promptfoo, Inspect, or TruLens.
- Experience with LLM observability and tracing tooling such as LangSmith, Langfuse, Braintrust, or Arize Phoenix.
- Statistical literacy: A/B testing, significance, and sample sizing for model and prompt comparisons.
- A background in machine learning or data science, or experience collaborating closely with those who do.
- Experience with the problem domain: FME, other ETL tools, spatial data processing, or data integration.
Retrieval and infrastructure:
- Working knowledge of embeddings, vector databases (e.g. pgvector), and chunking and retrieval strategy.
- Experience with Docker and deploying applications on Kubernetes.
- Experience working with services from a cloud provider, such as AWS, GCP, or Azure.
- Understanding of common client and server side vulnerabilities (e.g. OWASP Top 10) as well as security vulnerabilities specific to LLM–based applications.
WHAT YOU CAN EXPECT
When you choose a career with Safe Software, you’re also choosing…
- Meaningful Work: Make a profound impact across our business, workplace and data integration product.
- A Supportive Environment: Feel empowered to share your ideas and implement them with high autonomy and team support.
- Social Responsibility: Become part of a team that finds meaningful ways to give back https://www.safe.com/about/community-initiatives/. Take paid time off to volunteer for one of our Safe-organized opportunities that align with our core community initiatives.
- Learning & Career Development: We believe in your continuous learning and growth. Take advantage of an annual learning budget and training programs paid for by Safe.
- Flexible Working Hours: Flexible and remote-friendly work arrangements to fit your lifestyle. Work when you want, and how you want to.
- Work-Life Balance: There's no place for burnout at Safe. Maintain a healthy balance of your personal and work life without splitting yourself in two. Enjoy 3 weeks of vacation to recharge, plus an additional paid 6 seasonal days off per year.
- Health & Wellness: Extended health, dental, health or lifestyle spending, and counseling benefits from day 1. That’s right, no waiting period.
- Family is important: We are dedicated to supporting our employees through parenthood and offer a Parental Leave Top-Up Program for new parents through childbirth or adoption.
- Shared Success: Share in Safe’s success with our bi-annual profit sharing and RRSP/TFSA matching program.
- An Accessible Commute: Regardless of your commute method, we’re located close to public transit, and provide complimentary parking and bike storage for our team!
ABOUT SAFE SOFTWARE
Safe Software transforms organizations with FME, the only All-Data Any-AI Enterprise Integration Platform connecting all your data, anywhere, at any velocity.
With over 30 years of expertise and 25,000+ enterprise customers across 125+ countries, we simplify your data journey, wherever it leads.
Founded in 1993, Safe is headquartered in Surrey, BC with over 300 team members and counting. We’re always looking for talented individuals with diverse backgrounds who are determined to learn and grow. Are you ready to join the team?
OUR COMMITMENT TO DIVERSITY AND INCLUSION
Safe Software is an equal opportunity employer and we truly believe that innovation and strength begin with diversity and inclusion.
We welcome all candidates regardless of race, gender identity or expression, sexual orientation, age, ability, disability, national or ethnic origin, political belief, religion, or family status.
Should you require accommodations during the recruitment process, please contact hr_dept@safe.com.
NOTICE REGARDING USE OF AUTOMATED TOOLS IN HIRING
At Safe Software, we use automated tools to help us process applications and identify qualified candidates. These tools may assist in screening resumes and summarizing interview content based on the information you provide. This helps our team review applications efficiently while ensuring every candidate is considered based on the requirements of the role.
Please be assured that the final hiring decision is always made by a member of our team. For more information on how we protect your privacy, please see our policy https://www.safe.com/legal/#applicant-privacy-policy. If you have questions about this process, please contact us at hr_dept@safe.com.
Location: San Francisco, CA | New York City, NY
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures.
We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained.
This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job.
Key responsibilities
Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval
Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online
Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation
Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation
Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality
Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture
Minimum qualifications
Proficiency in Python and SQL
Experience training machine learning models and deploying them to production
Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow)
Working understanding of point-in-time correctness and training / serving skew, and how to prevent both
Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders
Preferred qualifications
Experience building or operating a feature platform such as Chronon, Feast, or Tecton
Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams
Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking
Experience with tree-based models on tabular data
Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse
Experience in integrity, spam, fraud, or abuse detection
Experience working with scarce, delayed, or noisy labels
Experience with AutoML or other approaches to automating the ML workflow
Care about the societal impacts of AI and want your work to make powerful systems safer
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.
Our engineers are extremely high leverage: we simultaneously drive multiple major revenue streams while optimizing one of Anthropic's most precious resources: compute. As we expand to more cloud platforms, the complexity of managing inference efficiently across providers with different hardware, networking stacks, and operational models grows significantly. We need product-minded backend engineers who can navigate these platform differences, design the services and abstractions that work across providers, and make architectural decisions that keep us reliable and cost-effective at massive scale.
Your work will increase the scale at which our services operate, accelerate our ability to reliably launch new frontier models and innovative features to customers across all platforms, and ensure our LLMs meet rigorous safety, performance, and security standards.
Key responsibilities
Design, build, and own backend services and infrastructure that serve Claude across multiple CSPs, accounting for differences in compute hardware, networking, APIs, and operational models
Work cross-functionally with internal inference, product API, systems, and security teams, among others, and with CSP partners to stand up the full serving stack on new cloud platforms, resolve operational issues, and influence provider roadmaps
Build and evolve CI/CD automation systems, including validation and deployment pipelines, that reliably ship new model versions to millions of users across cloud platforms without regressions
Design interfaces and tooling abstractions across CSPs that enable cost-effective inference management, scale across providers, and reduce per-platform complexity
Contribute to capacity planning, autoscaling, and workload routing strategies that match supply with demand and direct requests to the most cost-effective accelerator and region
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Minimum qualifications
Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
Are curious about LLM serving; prior inference or ML experience is not required
Thrive in cross-functional collaboration with both internal teams and external partners
Have experience working with external partners to align goals and deliver impact
Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description
Preferred qualifications
Direct experience working with CSPs to scale infrastructure or products across multiple platforms, navigating differences in networking, security, privacy, billing, and managed service offerings
Hands-on experience with capacity management, cost optimization, or resource planning at scale across heterogeneous environments
Solid understanding of multi-region deployments, geographic routing, and global traffic management
Proficiency in Python or Rust
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: San Francisco, CA | Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
The Cloud Inference team scales and optimizes Claude to serve the massive audiences of developers and enterprise companies across AWS, GCP, Azure, and future cloud service providers (CSPs). We own the end-to-end product of Claude on each cloud platform, from API integration and intelligent request routing to inference execution, capacity management, and day-to-day operations.
Within Cloud Inference, the model & inference launch team owns the validation pipeline for our inference server and load balancer on these platforms. We're responsible for every inference change — model launches, performance improvements, safeguard integrations — landing on cloud platforms with correctness, performance, and reliability intact.
This is high-leverage infrastructure work: validation has to be fast and cheap enough to run on the same accelerators that serve customers, trustworthy enough to replace manual checks, and consistent enough that a change working on Anthropic first-party means it works everywhere. This directly determines how fast frontier models and features ship to every cloud platform, and how quickly performance wins reach production — reclaiming capacity at a time when compute is our scarcest resource.
Key responsibilities
Be on the critical path for frontier model launches, bringing up inference for new model architectures and shipping them to cloud platforms in lockstep with our first-party platform
Work with the core inference team to bring new inference features (e.g. structured sampling, prompt caching, and more) to cloud platforms, owning the platform-specific integration that gets them to production
Identify and dive deep on the gaps that make inference behave differently across first-party and CSPs — config drift, observability, deployment patterns, hard cross-platform bugs — and fix them at the source rather than building platform-specific workarounds
Design, build, and own the CI/CD infrastructure for the inference server and load balancer across cloud platforms, with shadow traffic, performance baselines (throughput and latency), and correctness checks that catch regressions before production
Drive down merge-to-production cycle time by making validation faster, more parallel, and cost-effective enough to run on the same constrained accelerator pool that serves customers, without trading away reliability
Analyze observability data across providers to identify performance bottlenecks, cost anomalies, and regressions, and drive remediation based on real-world production workloads
Minimum qualifications
Have a strong interest in LLM serving; prior inference or ML experience is not required
Have significant software engineering experience, with a strong background in high-performance, large-scale distributed systems serving millions of users
Have a track record of building automation or test infrastructure that measurably improved release velocity or reliability
Have experience building or operating services on at least one major cloud platform (AWS, GCP, or Azure), with exposure to Kubernetes, Infrastructure as Code, or container orchestration
Thrive in cross-functional collaboration with both internal teams and external partners
Are a fast learner who can quickly ramp up on new technologies, hardware platforms, and provider ecosystems
Are highly autonomous and take ownership of problems end-to-end, including work that falls outside your job description
Preferred qualifications
LLM inference optimization, batching, and caching strategies
Capacity-constrained scheduling or shared-resource test infrastructure
Solid understanding of multi-region deployments, request routing, load balancing, global traffic management
Working with CSP partner teams to scale infrastructure across multiple platforms, navigating differences in networking, security, privacy, and managed service
Proficiency in Python or Rust
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: New York City, NY; San Francisco, CA; Seattle, WA
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.
The team has a dual mandate:
maximizing compute efficiency
to reliably serve our explosive customer growth, while
enabling breakthrough research
by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.
Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems.
Key responsibilities
Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide
Develop resilient, flexible systems that adapt in real time to real world events
Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers
Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers
Build and operate production-grade deployment pipelines for releasing new models to users
Provide high-performance inference infrastructure that enables researchers to develop next-generation models
Integrate new AI accelerator platforms and support inference for new model architectures
Minimum qualifications
Significant software engineering experience, particularly with distributed systems
Results-oriented, with a bias towards flexibility and impact
Willingness to pick up slack, even if it goes outside your job description
Desire to learn more about machine learning systems and infrastructure
Thrive in environments where technical excellence directly drives both business results and research breakthroughs
Care about the societal impacts of your work
Preferred qualifications
Experience with high-performance, large-scale distributed systems
Experience implementing and deploying machine learning systems at scale
Experience with load balancing, request routing, or traffic management systems
Familiarity with LLM inference optimization, batching, and caching strategies
Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)
Proficiency in Python or Rust
Representative projects
Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments
Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads
Building production-grade deployment pipelines for releasing new models to millions of users reliably
Contributing to new inference features
Supporting inference for new model architectures
Analyzing observability data to tune performance based on real-world production workloads
Managing multi-region deployments and geographic routing for global customers
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$320,000
—
$485,000 USD
Logistics
Minimum education:
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study:
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience:
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy:
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship:
We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
For roles performing work in California:
We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit
anthropic.com/careers
directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage:
Learn about
our policy
for using AI in our application process.
Location: Remote Canada
At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.
Affirm’s Identity team is mission-critical to the customer checkout experience. When a customer chooses Affirm, one of the first steps is an identity check, and our ability to make the right decision directly impacts conversion, revenue, fraud exposure, and regulatory compliance. Our team owns Identity for all markets outside North America, playing a key role in Affirm’s international expansion. We are responsible for KYC, user lifecycle management, and identity decisioning across multiple regulatory environments. This work is about shaping how Affirm adapts its core Identity platform to new market dynamics, customer expectations, and compliance requirements.
What you'll do
You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects.
You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed.
You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes.
You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts.
You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks.
You will help develop talent on your team by providing feedback and guidance, and leading by example.
What we look for
You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin.
You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes.
You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others.
You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work.
Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers.
You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
Base Pay Grade
- P
Equity Grade
- 7
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).
CAN base pay range per year:
CAD $181,000 - $241,000
Location - Remote Canada
This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan.
#LI-Remote
Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.
Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:
Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.
For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.
By clicking "Submit Application," you acknowledge that you have read Affirm's
Global Candidate Privacy Notice
and consent to the use of your personal information as described.
Location: Remote US
At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.
Affirm’s Identity team is mission-critical to the customer checkout experience. When a customer chooses Affirm, one of the first steps is an identity check, and our ability to make the right decision directly impacts conversion, revenue, fraud exposure, and regulatory compliance. Our team owns Identity for all markets outside North America, playing a key role in Affirm’s international expansion. We are responsible for KYC, user lifecycle management, and identity decisioning across multiple regulatory environments. This work is about shaping how Affirm adapts its core Identity platform to new market dynamics, customer expectations, and compliance requirements.
What you'll do
You will be responsible for setting technical strategy for your team on a year-long time scale, and help your team tie it together with critical, business-impacting projects.
You will collaborate across teams in the product development lifecycle by collaborating with product management, design & analytics to ensure technical sustainability, risks and trade-offs are well understood and managed.
You will act as a force-multiplier for your team through your definition and advocacy of technical solutions and operational processes.
You take ownership of your team’s operations and availability by ensuring you have the right monitoring, triage rotations, playbooks, polcities, testing and alerting in place to support “keep the lights on” & on-call efforts.
You will foster a culture of quality and ownership on your team by setting code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks.
You will help develop talent on your team by providing feedback and guidance, and leading by example.
What we look for
You have 8+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin.
You have an extensive track record of developing highly available distributed systems using technologies like AWS, MySQL, Spark and Kubernetes.
You have experience delivering major features, system components or deprecating existing functionality in a system through the definition of a technical and execution plan. You write high quality code that is easily understood and used by others.
You thrive in ambiguity, and are comfortable moving from low level language idioms all the way to the architecture of large systems to understand how they work.
Your growth and impact trajectory demonstrates that you have mastered gathering and iterating on feedback from your engineering and cross-functional peers.
You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
Base Pay Grade
- P
Equity Grade
- 13
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA Pacific base pay range (CA, WA, NY, NJ, CT):
$230,000 - $290,000
USA Sapphire base pay range (all other U.S. states):
$204,00 - $264,000
#LI-Remote
Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.
Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:
Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.
For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.
By clicking "Submit Application," you acknowledge that you have read Affirm's
Global Candidate Privacy Notice
and consent to the use of your personal information as described.
Location: Los Angeles, USA
Riot engineers bring deep knowledge of specific technical areas but also value the opportunity to work in a variety of broader domains. As Software Engineers, we work with both new and current technology, creating innovative solutions to overcome high-volume obstacles and to deliver player value.
As part of the Riot Infrastructure Team, you’ll join a core group of engineers responsible for building and evolving the infrastructure that enables Riot’s games to operate globally at scale. As a
Staff Software Engineer
on the Infrastructure team, you’ll focus on reducing toil and inefficiency for Riot engineers through tooling and automation, particularly as we explore new opportunities enabled by AI. The solutions you build could range from Slack bots, AI agents, and MCP servers to systems that automate game deployments and other critical workflows. You’ll collaborate with teams across Infrastructure and throughout Riot to identify high-impact problem areas, shape technical solutions, and build tools and automation that make a meaningful difference in how engineers get their work done.
Responsibilities:
Design solutions and features based on requirements and agreements with our stakeholders using our standard frameworks and best practices
Drive improvements to our standards and best practices where necessary
Continually looking for efficiency and improvement opportunities within our infrastructure, propose solutions and rally support for your proposal.
Work with senior leadership across organizations to ensure successful implementation
Lead by example on quality design and coding standards
Help grow the team through mentoring and leveling up of less experienced teammates
Build healthy relationships with other engineering teams at Riot to foster cross-team collaboration.
Required Qualifications:
7+ years experience as a software engineer with focus on infrastructure or tooling in a fast-paced, large-scale environment
Expertise with full software development life cycle
Expertise in one or more object oriented languages (i.e. Python, Go, Java, C++)
Strong experience working with containers and Kubernetes
Experience with large-scale development/deployment on Cloud (i.e. AWS/GCP)
Experience with large-scale Deployment technologies (i.e. Cloudbees Jenkins, GitHub Actions)
Experience with AI tools such as Codex, Windsurf, Co-Pilot
Understand core infrastructure services, distributed systems, microservices, and software at a large scale
Desired Qualifications:
Experience in fast pasted and matrixed organizations
Experience operating and supporting agile development, production services, and high availability
Understand networking - HTTP down to the network layer (TCP/IP, routing, etc.)
Experience working with international team members and colleagues
For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position!
Our Perks:
Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our
benefits pages
for more information.
At Riot Games, we
put players first
. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.
It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
Safeguarding confidential and sensitive Company data
Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
Accessing Company assets, secure digital systems, and networks
Ensuring a safe interactive environment for players and other Rioters
These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.
Location: United States
Workplace: Remote
About Cantina:
Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role:
Cantina is a place where people create AI characters and the videos those characters star in, and the catalog grows far faster than anyone can browse. Search and recommendations are what turn that catalog into a product: they decide which characters a new user meets in their first minute, which creators get discovered, and what appears in every feed, leaderboard, and discovery surface we ship. We are hiring a Senior Staff Software Engineer to own that area end to end — retrieval, ranking, relevance quality, and the roadmap for all three. This is the first dedicated hire for search and recommendations, so you will inherit a real production system serving live traffic along with a large amount of unclaimed ground, and you will set the technical direction rather than execute someone else’s.
What you'll do:
- Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards.
- Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships.
- Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time.
- Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface.
- Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them.
- Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended.
- Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it.
- Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it.
What you'll bring:
- 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product.
- Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it.
- A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why.
- Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online.
- Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines).
- Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result.
- Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency.
- Preferred: experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints.
Compensation:
The anticipated annual base salary range for this role is between $250,000 - $320,000 (USD). When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits:
- Competitive salary and generous company equity
- Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
- 42 days of paid time off, including:
- 15 PTO days
- 10 sick days
- 15 company holidays
- 2 floating holidays
- Generous parental leave & fertility support
- 401(k) retirement savings plan
- Lifestyle spending account – $500/month to use however you’d like
- Complimentary lunch and snacks for in-office employees
- One Medical membership, and more!
Location: Washington DC
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
Harvey is bringing its AI platform to the U.S. federal government — defense and civilian agencies whose legal, acquisition, and program teams are asking how to adopt AI responsibly. You will be Harvey's first Solutions Architect dedicated to public sector: the technical lead on federal opportunities, the person who designs how Harvey is deployed securely inside government environments, and the one who writes the playbook the rest of the team will follow.
You will sit at the intersection of Harvey's platform, agency stakeholders (legal, IT, security, acquisition, and program offices), and our Security & Trust, Legal Engineering, Product, and Customer Success teams. This is an opportunity to help define how AI is adopted across the federal government and to build a flagship public-sector practice at one of the fastest-moving companies in applied AI.
WHAT YOU'LL DO
- Lead technical discovery and solution design for federal prospects and customers — defense and civilian — working with legal, IT, security, acquisition, and program stakeholders.
- Design, document, and defend secure, compliant architectures for Harvey in government environments, including Harvey's FedRAMP High environment, identity and access patterns, integrations, and data-handling requirements (CUI, records retention, auditability).
- Own the technical thread on a focused portfolio of high-impact federal accounts, from first conversation through rollout, adoption, and expansion.
- Be the field-facing technical partner to Security & Trust on agency security reviews — FedRAMP High controls, DoD Impact Levels, ATO and authorization boundaries, NIST 800-53 — and translate them for program owners and counsel.
- Work with Legal Engineers and Customer Success Managers to turn agency workflows and legal or policy use cases into concrete solutions, reusable patterns, and implementation playbooks.
- Be the public-sector technical voice back into Harvey, synthesizing field feedback to inform roadmap, evaluation criteria, deployment options, and government-specific documentation.
- Represent Harvey's technical perspective in public-sector forums — customer workshops, working groups, and stakeholder briefings — helping agencies understand both the possibilities and the limits of current AI systems.
- Build the public-sector Solutions Architecture playbook — qualification, security review, deployment patterns, and enablement — so the practice can scale beyond one person.
WHAT YOU HAVE
- 7+ years in solutions architecture, sales engineering, forward-deployed engineering, or a similar customer-facing technical role.
- Direct experience selling to or supporting U.S. federal customers (Department of Defense and/or civilian agencies) at a SaaS or cloud provider, including navigating agency security reviews and procurement.
- Working knowledge of federal compliance frameworks and how they shape deployment — FedRAMP, NIST 800-53, DoD Impact Levels, ATO processes — and the ability to explain them to CISOs and program managers alike.
- Hands-on depth in SaaS security and identity architecture: SSO/SAML, SCIM, encryption and key management, data residency, audit logging.
- Clear communication with technical and non-technical audiences — from program managers and attorneys to CISOs and enterprise architects — and credibility with senior public-sector stakeholders.
- Hands-on engagement with modern AI systems (LLMs, prompt design, evaluation, deployment patterns) and a desire to help agencies adopt them responsibly.
- Comfort operating in an emerging practice area: energized by ambiguity, willing to build new playbooks, motivated by real-world impact on public services.
PREFERRED
- Prior government service or military experience.
- Experience with Azure Government or other government cloud environments.
- Experience selling through federal systems integrators or contract vehicles.
- Background in legal, e-discovery, or other document-heavy enterprise workflows.
COMPENSATION
$218,800 - $300,900 USD OTE with a 80/20 split
LOCATION
Remote within Washington, DC area - travel approximately 25–40% to agency and partner sites.
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-TM1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
United States - Remote
New York, NY, United States
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