Location: Remote
Dexis is a dynamic professional services firm dedicated to partnering with government and community leaders both in the U.S. and internationally to achieve critical social outcomes in a rapidly changing world.
At Dexis, you will experience a corporate culture of inclusiveness, respect, fairness, and trust. You will be given the means and mentorship needed to succeed, and your creativity will be rewarded.
About the Project
This project will provide a broad range of assessment, monitoring, and evaluation (AM&E) support to DSCA. Project tasks will include desk and field research, analysis, data collection and visualization, strategy development, policy writing and coordination, and AM&E capacity building.
Responsibilities
AM&E Analysts II will support the design, coordination, conduct, and reporting of Security Cooperation analyses. They will work with key stakeholders to ensure efforts stay up to date with emerging AM&E techniques, tools, and approaches in specific subject matter. Key responsibilities include:
Supporting the leadership team in identifying priorities and solutions to problems
Providing qualitative and quantitative analysis of security cooperation programs
Assisting with the development of indicators and metrics that enable evaluation of security cooperation programs
Drafting reports, presentations, and other deliverables for senior leadership review
Supporting the design and development of visual graphics (e.g., illustrations, layouts, designs) that distills key information in a clear, concise manner
Supporting the development and maintenance of project processes and plans
Travel up to 25-50% domestically and internationally as determined by client and portfolio requirements and demands on regional team, while adhering to approved budget, cost reasonableness requirements, and all applicable corporate and federal travel regulations
Qualifications
Bachelor’s degree
Four (4) years of AM&E experience, including analyzing and summarizing disparate information in a clear and concise manner, drafting data collection methodologies, creating organizational work plans based on higher-level goals, leading and coordinating multiple offices through multiple step processes without being a direct supervisor, and supporting staff with a variety of levels of knowledge and capabilities
Strong oral and written communication skills to deal effectively with mid and high-level partner contacts, the host government, and local communities
Ability to apply government agency regulations and procedures related to controlled unclassified information and foreign disclosure to daily work requirements
Excellent computer skills, including word processing, spreadsheet programs and data base management
Seven (7) years of AM&E or capability-based-assessment (CBA) or other types of experience in one or more of the following subject matters: counterterrorism operations; Counter-weapons of mass destruction operations; counter-illicit drug trafficking operations and counter-transnational organized crime operations; maritime and border security operations; military intelligence operations and Operations or activities that contribute to an international coalition operation that is determined by the Secretary to be in the national interest of the United States; air domain awareness operations; cyberspace security and defensive cyberspace operations; humanitarian assistance and demining; small-scale construction associated with any of the above mission areas; Security Sector Governance (both across each of the above program areas as well as through distinct programs focused solely on Security-related institutions that span these broad program areas)
DoD Secret clearance
Preferred Qualifications
Two (2) years of experience assessing, developing, mapping, and improving business processes
Five (5) years of experience and knowledge of public policy and operations
Five (5) years of experience planning, designing and implementing assessment, monitoring, and evaluation programs or projects in the security sector for a national organization, an NGO/IGO, the UN, or private industry
Master’s degree (or higher) and formal training or education in the field of assessment, monitoring, and evaluation
One to three (1-3) years of experience planning, executing, or overseeing policy of guidance for SC activities implemented under sections 332, 333, 1263, 342, 345, 401, or 2561 of Title 10, Chapter 16
Currently located in Hawaii or in the National Capital Region (NCR)
Below is the pay range aligned with this position. When developing a range, Dexis evaluates compensation holistically, triangulating between external market research
, our budget for the position, and internal equity to arrive at a figure that is fair and competitive. Offers within this range will be based on an individual candidate's qualification, relevant education and experience, skills, performance, and organizational needs.
Dexis pay range for this role:
$100,000
—
$124,000 USD
Benefits
Dexis offers benefits to support employees’ health, financial security, and well-being. The benefits outlined below are for
full-time, US-based
positions only. These benefits include:
Medical and prescription drug coverage:
A choice of three UnitedHealthcare medical plans, with coverage options for employees and eligible dependents.
Dental insurance:
Dental coverage for employees and eligible dependents, including preventive, basic, major, and orthodontic services, subject to plan limits.
Company-paid vision insurance:
Vision coverage for employees and eligible dependents, with premiums paid in full by Dexis.
Employer-funded health reimbursement arrangement (HRA):
Employees who enroll in the Silver HRA medical plan receive an employer-funded HRA to help pay eligible in-network deductible expenses.
Company-paid life and disability insurance:
Basic life and accidental death and dismemberment (AD&D) insurance, plus short-term and long-term disability coverage.
Optional supplemental insurance:
Voluntary supplemental life and AD&D insurance options, including life insurance options for eligible dependents.
Employee Assistance Program (EAP):
Company-paid access to confidential counseling and legal and financial support resources for employees and their families.
Health and wellness resources:
Virtual care, behavioral health resources, and wellness programs available through the medical plan.
Benefits assistance:
Personalized support with benefit enrollment, coverage questions, claims, and finding providers through the Employee Care Center.
Participation, coverage, and employee contributions are subject to applicable benefit plan terms and eligibility requirements.
Dexis is on a mission to help solve today’s most pressing global political, social, and economic challenges and create a world where all people are safe and prosperous. As a Dexis employee, you will be challenged, empowered, and mentored. Our motto is “find a way or make a way” — that’s how Dexis goes “all in.” How will you?
If you are passionate about this opportunity, apply now!
Only those applicants who meet the above criteria will be contacted for interview.
Dexis is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, sex, national origin, religion, pregnancy, disability, age, genetic information, military service, veteran status, ethnicity, citizenship, sexual orientation, gender identity, marital status, childbirth and related medical conditions, including lactation, or any other protected class under applicable law.
Location: San Francisco, CA • New York, NY • United States
Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
We’re hiring a Researcher, AI Evaluations to join AI Insights within Figma’s Research team. This is a senior individual contributor role with no direct reports, reporting to the AI Insights lead and working directly with AI Research within AI Platform. You’ll strengthen the team’s model, agent system, and evaluation work through hands-on studies, clear rubrics, and reliable measures of quality that reflect user needs, and your findings will guide model and product improvements.
This is a full time role that can be held from one of our US hubs or remotely in the United States.
What you’ll do at Figma:
Own evaluation research for priority AI Research workstreams. Define quality criteria, design studies, analyze results, and recommend actions
Build rubrics, representative evaluation datasets, benchmarks, and quality thresholds that reflect user needs and expert design judgment
Work with AI Research and Modeling Platform engineers to integrate validated methods into repeatable evaluations and regression tests
Explain quality, failure patterns, and uncertainty. Recommend actions that guide model selection, model improvements, product priorities, and release decisions
Validate automated graders against human ratings, including LLM-as-judge methods that use a large language model to score outputs. Identify bias, gaps, and uncertainty
Connect user research with AI Research’s model development work. Share reusable methods, review work, and mentor peers
We’d love to hear from you if you have:
7+ years of experience in research, applied research, or a related field, with a proven track record of independently leading complex evaluation projects and delivering measurable impact
Hands-on experience evaluating AI products, with demonstrated ability to translate evaluation findings into meaningful model and product improvements
Expertise in designing human evaluations, scoring rubrics, datasets, and benchmarks, including measuring inter-rater agreement and validating automated graders
Strong qualitative and quantitative research skills, with the ability to analyze data, interpret uncertainty, and draw actionable insights into model behavior and performance
Excellent problem-solving and stakeholder management skills, with the ability to navigate ambiguity, prioritize risks, balance speed with rigor, and deliver recommendations that influence cross-functional decisions
While it’s not required, it’s an added plus if you also have:
Experience integrating automated evaluations and regression testing into engineering workflows, with familiarity in tools such as Braintrust, LangSmith, DeepEval, or equivalent platforms
Proven ability to develop scalable, reusable evaluation frameworks and drive the adoption of consistent quality standards across teams
Background in product design, product management, data science, or engineering, with familiarity in Figma or similar design and developer tools
Strong statistical expertise in sampling, significance testing, and agreement metrics, with experience conducting experiments or analyzing performance metrics for AI-powered features
Advanced training in a quantitative or behavioral discipline, gained through formal education or equivalent hands-on experience
At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Pay Transparency Disclosure
Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location.
Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law.
Annual Base Salary Range:
$169,000
—
$250,000 USD
At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an
equal opportunity workplace
- we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
,
or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to
accommodations-ext@figma.com
. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
Examples of accommodations include but are not limited to:
Holding interviews in an accessible location
Enabling closed captioning on video conferencing
Ensuring all written communication be compatible with screen readers
Changing the mode or format of interviews
To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with
Figma's Candidate Privacy Notice
.
Application limits:
To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles:
Candidates may submit up to 5 applications during any rolling 30-day period.
Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection.
Once the applicable days has passed, candidates are welcome to apply again.
Location: Indonesia; Nigeria; Turkey; United States
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are looking for experienced Application Security Engineers and Security-Focused Software Engineers to support a specialized AI security evaluation project.
In this role, you will assess how effectively static analysis tools identify security vulnerabilities in Generative AI applications, particularly LLM agents and Retrieval-Augmented Generation (RAG) systems. You will build small, runnable repositories containing realistic examples of Sensitive Information Disclosure (SID) and Excessive Agency (EA) vulnerabilities, alongside fixed and near-miss versions.
You will analyze code paths, identify security weaknesses, define authorization contexts, develop deterministic tests, and document findings. Your work will help improve the reliability of security tools and strengthen how AI systems are evaluated for application-level vulnerabilities.
LOCATION:
Remote
EXPERIENCE:
5+ years in application/product security or security-focused software engineering
PROJECT:
GenAI application security evaluation and AI training
TECHNICAL FOCUS:
Python, TypeScript, SAST, CodeQL, Semgrep, LLM agents, RAG, and MCP
AI EXPERIENCE:
Hands-on experience building LLM agents or RAG applications is required.
Key Responsibilities
Build runnable agent and RAG repositories containing code-reachable Sensitive Information Disclosure and Excessive Agency vulnerabilities.
Develop realistic security scenarios involving tool calling, agent memory, Model Context Protocol (MCP), and other LLM application components.
Create vulnerable, fixed, and hard-negative code variants with minimal security-relevant differences.
Evaluate static application security testing (SAST) tools and assess their ability to detect genuine vulnerabilities while avoiding false positives.
Perform source-to-sink analysis and trace relevant data flows, action paths, and trust boundaries.
Annotate security findings, including affected assets, root causes, controls, severity, and residual risk.
Define authorization contexts covering actors, tenants, identities, permitted data, actions, purposes, and recipients.
Develop deterministic tests to validate vulnerable, fixed, and negative security behaviors.
Recommend appropriate security controls and remediation approaches.
Participate in technical calibration, peer reviews, and quality assurance activities.
Requirements
5+ years of professional experience in application security, product security, or security-focused software engineering.
Strong experience conducting secure code reviews and identifying application-level vulnerabilities.
Practical knowledge of source-to-sink analysis, taint analysis, and static application security testing (SAST).
Hands-on experience with security analysis tools such as CodeQL or Semgrep.
Experience building or securing LLM agents and/or Retrieval-Augmented Generation (RAG) applications.
Familiarity with frameworks and technologies such as LangChain, LlamaIndex, OpenAI or Anthropic SDKs, and Model Context Protocol (MCP).
Strong understanding of authorization models, including:
Actors, identities, and trust boundaries.
Multi-tenant authorization and access control.
OAuth, IAM, and identity management.
Permitted data access and actions.
Purpose and recipient restrictions.
Document-level access control.
Production-level coding experience in Python and/or TypeScript.
Ability to distinguish genuine Sensitive Information Disclosure and Excessive Agency vulnerabilities from non-findings and false positives.
Strong analytical skills and the ability to communicate technical security findings clearly.
Location: Bangladesh; Brazil; Colombia; Egypt; Ghana; India
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are looking for experienced Application Security Engineers and Security-Focused Software Engineers to support a specialized AI security evaluation project.
In this role, you will assess how effectively static analysis tools identify security vulnerabilities in Generative AI applications, particularly LLM agents and Retrieval-Augmented Generation (RAG) systems. You will build small, runnable repositories containing realistic examples of Sensitive Information Disclosure (SID) and Excessive Agency (EA) vulnerabilities, alongside fixed and near-miss versions.
You will analyze code paths, identify security weaknesses, define authorization contexts, develop deterministic tests, and document findings. Your work will help improve the reliability of security tools and strengthen how AI systems are evaluated for application-level vulnerabilities.
LOCATION:
Remote
EXPERIENCE:
5+ years in application/product security or security-focused software engineering
PROJECT:
GenAI application security evaluation and AI training
TECHNICAL FOCUS:
Python, TypeScript, SAST, CodeQL, Semgrep, LLM agents, RAG, and MCP
AI EXPERIENCE:
Hands-on experience building LLM agents or RAG applications is required.
Key Responsibilities
Build runnable agent and RAG repositories containing code-reachable Sensitive Information Disclosure and Excessive Agency vulnerabilities.
Develop realistic security scenarios involving tool calling, agent memory, Model Context Protocol (MCP), and other LLM application components.
Create vulnerable, fixed, and hard-negative code variants with minimal security-relevant differences.
Evaluate static application security testing (SAST) tools and assess their ability to detect genuine vulnerabilities while avoiding false positives.
Perform source-to-sink analysis and trace relevant data flows, action paths, and trust boundaries.
Annotate security findings, including affected assets, root causes, controls, severity, and residual risk.
Define authorization contexts covering actors, tenants, identities, permitted data, actions, purposes, and recipients.
Develop deterministic tests to validate vulnerable, fixed, and negative security behaviors.
Recommend appropriate security controls and remediation approaches.
Participate in technical calibration, peer reviews, and quality assurance activities.
Requirements
5+ years of professional experience in application security, product security, or security-focused software engineering.
Strong experience conducting secure code reviews and identifying application-level vulnerabilities.
Practical knowledge of source-to-sink analysis, taint analysis, and static application security testing (SAST).
Hands-on experience with security analysis tools such as CodeQL or Semgrep.
Experience building or securing LLM agents and/or Retrieval-Augmented Generation (RAG) applications.
Familiarity with frameworks and technologies such as LangChain, LlamaIndex, OpenAI or Anthropic SDKs, and Model Context Protocol (MCP).
Strong understanding of authorization models, including:
Actors, identities, and trust boundaries.
Multi-tenant authorization and access control.
OAuth, IAM, and identity management.
Permitted data access and actions.
Purpose and recipient restrictions.
Document-level access control.
Production-level coding experience in Python and/or TypeScript.
Ability to distinguish genuine Sensitive Information Disclosure and Excessive Agency vulnerabilities from non-findings and false positives.
Strong analytical skills and the ability to communicate technical security findings clearly.
• Create and solve realistic full-stack tasks involving user-facing features and APIs. • Trace requests and data across browsers and back-end services to judge whether an AI implementation works correctly.
Vultr is looking for a Physical Security Evaluator to evaluate data-center security, document vulnerabilities, support mitigation, and report on physical security posture.
Location: London, United Kingdom
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
In a rapidly evolving world, trust in AI depends on agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible.
We’re looking for an experienced Data Analyst who has built evaluation systems for complex technology products and is excited to take end-to-end ownership of quality in search built for AI agents.
This role combines hands-on engineering, analytical judgment, and mathematical rigor, with the scope and influence to shape both technical decisions and product direction. We move at a startup pace, with plenty of open questions and difficult problems to solve.
In this position, you will:
• Own the quality measurement and improvement cycle end-to-end: identify user needs, define success, build evaluations, diagnose failures, and work with engineers and product managers to improve outcomes..
• Design, build, and evolve evaluation systems, including datasets, benchmarks, metrics, and automated pipelines that support development and launch decisions..
• Evaluate response quality across multiple dimensions, including relevance, completeness, freshness, factual accuracy, and usefulness to downstream agents..
• Investigate quality regressions and metric anomalies, uncover root causes, and identify the improvements with the greatest potential impact..
• Help prioritize the product and engineering roadmap, making quality trade-offs explicit and assessing whether changes deliver meaningful improvements for users..
We expect you to have:
• Substantial hands-on experience designing and building evaluation or quality measurement systems for complex technology products, such as search, AI agents, voice technologies, autonomous driving, recommendation systems, advertising, or other similar complex systems..
• A track record of owning ambiguous problems from initial framing through implementation, diagnosis, and measurable product improvement..
• Strong Python skills and an engineering mindset: you can turn analytical ideas into reliable, maintainable pipelines and tools..
• A solid foundation in mathematical statistics and practical experience with experimental design, sampling, uncertainty, and measurement bias..
• Strong analytical judgment: you understand what a metric captures, what it misses, and whether an observed improvement matters to users..
• The ability to reason across user needs, product behavior, and technical systems, and to translate that understanding into actionable evaluations..
• Strong communication and collaboration skills, with the ability to influence technical and product decisions..
• The independence to make progress in a fast-moving environment where requirements, methods, and definitions of success are still evolving.
Benefits & Perks:
Competitive compensation
Career growth and learning opportunities
Flexibility and ownership
Collaborative and innovative culture
Opportunity to work on impactful AI projects
International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Evaluate clinical EHR vignettes paired with a question, a proposed answer, and a distractor “trap” answer across diagnosis and treatment tasks, spanning cardiovascular, nervous, hematologic, respiratory, digestive, urinary, reproductive, musculoskeletal, and integumentary systems;
Location: Москва
Мы помогаем государству проводить disrupt госуправления через внедрение AI/GenAI и ускорять национальное развитие AI/GenAI, организуем одно из крупнейших в мире профильных мероприятий – AIJourney, объединяем бизнес, государство и международное научное сообщество, чтобы обеспечить GenAI-трансформацию страны.
Обязанности
• cтроить и развивать систему оценки качества LLM, RAG и агентов: тестовые наборы, метрики, автоматические прогоны, отчёты
• проводить регрессионное тестирование в CI при смене моделей, промптов и настроек, контролировать качество перед релизами и показами
• оценивать агентов по траекториям: успешность задач, ошибки вызова инструментов, лишние шаги
• калибровать автоматическую оценку (LLM-as-a-judge) против экспертной разметки
• строить пайплайны обработки документов: PDF, сканы, OCR, таблицы, восстановление структуры
• готовить датасеты для дообучения, включая синтетические данные и траектории вызова инструментов.
Требования
• от 3 лет в Data Science, Data Engineering или ML, из них не менее года с LLM-проектами
• опыт построения с нуля системы оценки качества LLM или RAG
• знание метрик поиска (recall@k, MRR, nDCG) и метрик ответов (faithfulness, полнота, корректность)
• опыт оценки агентных систем или многошаговых сценариев
• прикладная статистика: доверительные интервалы, значимость различий, размер выборки
• опыт обработки реальных документов в продакшене, включая OCR
• Python на уровне production-кода, уверенный SQL
• оркестрация пайплайнов (Airflow, Prefect, Dagster или аналоги), версионирование данных и трекинг экспериментов (DVC, MLflow или аналоги).
**Будет плюсом:**
• работа с юридическими, нормативными или канцелярскими текстами на русском языке
• классический NLP: NER, классификация, извлечение сущностей
• опыт с русскоязычными бенчмарками
• работа с персональными данными по 152-ФЗ
• Elasticsearch, OpenSearch, векторные базы данных.
Условия
* гибридный формат работы (м Кутузовская)
* ежегодный пересмотр зарплаты, годовой бонус
* корпоративный спортзал и зоны отдыха
* более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
* расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа
* гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
* подписка Прайм с возможностью совместного использования на трёх близких
* вознаграждение за рекомендацию друзей в команду Сбера
* корпоративная пенсионная программа.
Location: Japan
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: France
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: Egypt
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: Germany
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: Netherlands
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: South Korea
Workplace: remote
Join a short, paid project that tests whether AI coding agents work as well on instructions written in the target language as they do in English. Your language skills and technical background decide where you fit.
About the project
Welo Data is helping evaluate how well AI coding agents perform when the instructions they receive are written in languages other than English. Agents are given a real software engineering task in a code repository, and automated tests check whether they solved it. The code, repositories and tests stay exactly as they are. Only the human-written instructions change language, so the quality of every instruction directly affects the result.
About the roles
There are two roles on this project. We place you in one of them based on your experience& skillsets.
Translator: translate English software engineering task briefs into the target language. You keep every requirement, constraint and success condition, and you leave commands, file paths, API names, code and test conditions exactly as written in English. This role suits people with a stronger technical background, and translation experience is a plus.
Why Join Welo Data?
✨ Limitless Flexibility
Project-based opportunities that fit your availability. Choose when and how much you want to contribute—fully remote, with complete autonomy.
🌱 Limitless Growth
Optional access to AI and Large Language Model workshops designed specifically for professionals like you. No coding required—just your expertise.
🌍 Limitless Support
Be part of a global contributor community with responsive guidance and support.
💡 Real Impact
Apply your expertise in the Legal field to influence the AI systems shaping the future of your industry—while collaborating with data professionals and expanding your skills.
How to Apply?
Apply now by answering a few quick questions to join our database and become part of our growing community.
About Welo Data
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Location: New York, NY (HQ); San Francisco, CA
Workplace: Hybrid
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.
The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
ABOUT RAMP LABS
Ramp Labs is Ramp's AI research group. We post-train models on finance work, build the environments and evals they learn from, and ship them into the products 70,000+ companies use to move money. We think the defensible part of an AI product is the loop: proprietary environments, evals that track what customers care about, and models trained against both.
ABOUT THE ROLE
Every model decision at Ramp Labs runs through a benchmark. Which model to route to. Whether a post-training run worked. Whether an agent is ready to post a corrective journal entry to a customer's ledger without a human in the loop.
You'll own Ramp's benchmarking effort. You'll turn real finance work (expense policy review, invoice coding, month-end close, spreadsheet Q&A) into benchmarks and RL environments, build the graders, and tell the team what is actually improving.
WHAT YOU’LL DO
- Build benchmarks from real workflows: turn agent traces, customer edge cases and expert labels into versioned benchmark suites for long-horizon agents that run for hours across tools and systems, plus tool use, multi-step reasoning and financial judgment
- Own the benchmarking effort: decide what we measure, run benchmark suites across models and agent versions, and report results the team makes decisions on
- Design graders: rubrics, programmatic checks and llm-as-judge, calibrated against human agreement, with a clear view of where each one breaks
- Close the loop with post-training: turn evals into reward functions and RL environments, and catch reward hacking and contamination before they ship
- Publish external benchmarks and write-ups on how models perform at real finance work
WHAT YOU NEED
- Hands-on experience building LLM benchmarks or evals that people used to make real decisions
- Strong Python and software engineering; your eval code is reproducible and fast
- Statistical judgment: variance, confidence intervals, sample size, inter-rater agreement, and knowing when a delta is noise
- Working knowledge of post-training (SFT, RL with verifiable rewards) and how evals feed into it
- Comfort with SQL and large datasets; you'll work directly from production traces
- Taste for what is worth measuring
NICE-TO-HAVE
- Industry experience on an eval, benchmarking or post-training team
- Built RL environments or verifiers for agentic tasks
- Published benchmark or evaluation research (NeurIPS Datasets & Benchmarks, ICML, ACL)
- Built or contributed to eval frameworks (verifiers, lm-evaluation-harness, HELM or similar)
- Familiarity with accounting, finance or other expert-domain work
- Public work we can look at: a benchmark, an eval suite, a failure-analysis write-up
BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL)
- Flexible PTO
- Centralized home-office equipment ordering
- Health and wellness stipend
- Budget for intra-office travel
- Weekly coffee stipend
UNITED STATES
- 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
- One Medical annual membership
- 401(k), including employer match on contributions made while employed by Ramp
- Fertility HRA (up to $10,000 per year)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
- Pet insurance
- In-office perks: lunch, snacks, drinks, and more
- Relocation expense coverage to NYC or SF (if needed)
CANADA
- Group medical, dental, and vision coverage through Sun Life
- Life, AD&D, and disability coverage
- Fertility drug coverage (up to $4,000 lifetime)
- Group Retirement Plan with employer match (RRSP + DPSP)
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay
- Employee Assistance Program and virtual care through Lumino Health
UNITED KINGDOM
- Private medical insurance through Freedom Elite
- Virtual GP and at-home care via eMed x Livi
- Workplace pension through Penfold, with salary sacrifice option
- Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
REFERRAL INSTRUCTIONS
If you are being referred for the role, please contact that person to apply on your behalf.
OTHER NOTICES
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.
Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice
Location: London & San Francisco
Workplace: onsite
Application deadline: We are conducting interviews actively and aim to fill this role as soon as we find someone suitable.
ABOUT THE OPPORTUNITY
The OpenAI/Hugging Face incident may be the biggest warning shot we get before catastrophic loss-of-control. In its aftermath, Anthropic and OpenAI publicly committed to giving embedded evaluators an unprecedented level of access.
Embedded evaluations are the best existing method to find out whether alignment is on track. With OpenAI predicting an automated researcher by March 2028, we don't have time to start with an MVP embedded evaluation and iteratively improve it. The first embedded evaluations will set the standard and we have to get it right.
Apollo has taken steps toward becoming an embedded evaluator at frontier labs. We want to hire experienced senior researchers with a strong track record of getting things done to execute our embeddedevaluationplans.
KEY RESPONSIBILITIES
If embedded evaluations happen, you will be on one of the following teams:
On-site embedded evaluators:
This team will spend weeks or months embedded at a frontier AI lab, where they will conduct interviews, review the lab’s evidence, gather new evidence, and write a report. They will execute a playbook quickly and adapt to unforeseen circumstances. We hold our embedded evaluators to the highest standards, so you will likely have to first prove yourself within Apollo before being sent into an embedded campaign. That is, you will probably start on the applied research team to gain context on embedded evaluations. For this team, we prefer candidates with the right to work in the US who can be based in San Francisco.
Applied researchers:
This team will be the force-multiplier behind embedded evaluations. They will prepare on-site evaluators before they are embedded and support them while they are embedded. They will do the conceptual work to determine what evidence would support a safety case, and write the playbook for on-site evaluators to optimize how fast they can gather evidence. They will develop tooling for embedded evaluators, both ahead-of-time and urgently on demand. They will be the bridge connecting fundamental research and the on-site evaluators. For example, they might convert the methodology of
“Measuring Reward-Seeking via Contrastive Belief Updates”
into turnkey code and procedures. This team can work from any of our offices.
Both are high-stakes teams. On-site embedded evaluators should be exceptionally strong at quick execution under high pressure, and very strong at planning and research. Applied researchers should be exceptionally strong at planning and research, and very strong at quick execution under high pressure. For both teams, we are excited for experienced candidates who have owned ambitious projects end-to-end under tight deadlines.
KEY REQUIREMENTS
We don’t require a formal background or industry experience and welcome self-taught candidates. We assess demonstrated ability, including through independent research and nontraditional paths; prior formal management titles are not required.
Technical safety research judgment:
You have a strong track record of producing or leading technically rigorous research relevant to understanding and reducing risks from advanced AI. Your background might include alignment, interpretability, model evaluations, control, adversarial ML, or post-training. You understand modern model training well enough to interrogate a lab’s methods and learn unfamiliar pipelines quickly. Deep experience with frontier RL or post-training is valuable but not required.
Research leadership and delivery:
You have led ambitious technical projects end-to-end under hard deadlines and managed or closely supervised strong individual contributors (ICs). You can set research priorities, delegate meaningful ownership, review technical work, and keep a team focused on the questions that matter most.
Data Analysis & Pattern Recognition:
You can extract signal from large, messy datasets. You're comfortable with quantitative analysis and know when qualitative assessment is more appropriate. You can identify anomalies and unexpected model behaviors.
Writing for high-stakes audiences:
You have experience writing about qualitative and quantitative findings for different stakeholders. You can take a pile of unorganized technical information and communicate it effectively to lab safety teams, lab leadership, governments, or the public.
Strong understanding of scheming:
You have a strong conceptual understanding of ideas like metagaming, evaluation awareness, deception, and reward-seeking. You are familiar with classic literature like
Is Power-Seeking AI an Existential Risk?
and modern research.
AI power-user:
You’re capable of using AI to accelerate your work, technical or otherwise. You have experience using different models, know which ones to use for which tasks, when not to use AI, and always experiment with new AI workflows.
Professionalism:
You can represent Apollo independently in sustained, high-stakes technical collaborations. Your professional conduct is unimpeachable. You know when to tactfully resolve disagreements with partners and when to stand firm in negotiations, and you are excellent at both of those.
Mission commitment:
Apollo estimates that RSI will happen soon, and we are extremely concerned that AGI will catastrophically not be aligned with human values. Hence we have an “intense, but in a good way”
culture
. We will ask a lot from you, but in return you will personally have a large impact on loss-of-control risk.
NICE TO HAVES
Software engineering skills:
Strong software engineering skills correlate highly with effective execution, even in an era of AI agents. Our entire stack uses Python.
Prior embedded expertise:
You have previous experience in professional services like auditing or consulting. You’ve learned lessons from working on-site with clients that will generalize to working with frontier AI labs.
We want to emphasize that people who feel they don’t fulfill all of these characteristics but think they would be a good fit for the position, nonetheless, are strongly encouraged to apply. We believe that excellent candidates can come from a variety of backgrounds and are excited to give you opportunities to shine.
BENEFITS
This role offers a market-competitive salary, equity, and competitive benefits.
Depending on your experience, you may be offered a Lead or individual contributor position.
Salary:
Recognised experts who can lead projects of significant scope: USD 350,000 - USD 590,000 or £230,000 - £395,000
Strong individual contributors: USD 245,000 - USD 405,000 or £160,000 - £270,000
Unlimited vacation
Unlimited sick leave
Up to 6 months of paid parental leave
Comprehensive health, dental and vision insurance
Retirement savings with competitive employer matching (e.g. 401(k) for US employees)
Lunch, dinner, and snacks are provided for all employees on workdays
Paid work trips, including staff retreats, business trips, and relevant conferences
A yearly $1,000 (USD) professional development budget
Relocation support and visa fees (if applicable). We are able to sponsor visas to the UK and US.
LOGISTICS
Time Allocation
: Full-time
Location
: This is an in-person role working out of our London or San Francisco office.
We prefer on-site embedded evaluators to be permanently located in San Francisco.
Applied researchers can work from any of our offices. We offer flexible working hours and WFH arrangements. Remote candidates will only be considered if they are exceptional and can travel at least 1 week/month to either office.
Visa sponsorship:
We sponsor visas in both the UK and US. Sponsorship isn't guaranteed for every role or candidate, but if we make you an offer, we'll work with you to find the right visa route
ABOUT APOLLO RESEARCH
The rapid rise in AI capabilities offers tremendous opportunities, but also presents significant risks. At Apollo Research, we’re primarily concerned with risks from Loss of Control, i.e. risks coming from the model itself rather than e.g. humans misusing the AI. We’re particularly concerned with deceptive alignment / scheming, a phenomenon where a model appears to be aligned but is, in fact, misaligned and capable of evading human oversight.
We work on the detection of scheming (e.g., building evaluations and novel evaluation techniques), the science of scheming (e.g., model organisms and the study of scaling trends), and scheming mitigations (e.g., control). We closely work with multiple frontier AI companies, e.g. to test their models before deployment and collaborate on fundamental research.
At Apollo, we aim for a culture that emphasizes truth-seeking, being goal-oriented, giving and receiving constructive feedback, and being friendly and helpful. If you’re interested in more details about what it’s like working at Apollo, you can find more information here.
ABOUT THE TEAM
Alex Meinke leads the science of scheming team’s research agenda with guidance from Marius Hobbhahn, though team members lead individual projects. You will mostly work with the science of scheming team as well as our team of software engineers, but you will likely sometimes interact with the governance team to translate technical knowledge into concrete recommendations. You can find our full team here.
Equality Statement: Apollo Research is an Equal Opportunity Employer. We value diversity and are committed to providing equal opportunities to all, regardless of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation.
How to apply: Please complete the application form with your CV. The provision of a cover letter is optional but not necessary. Please also feel free to share links to relevant work samples.
About the interview process: Our multi-stage process includes a screening interview, 3 technical interviews, and a final interview with Marius (CEO). The technical interviews will be closely related to tasks the candidate would do on the job. There are no LeetCode-style general coding interviews. If you want to prepare for the interviews, we suggest (a) thinking about what embedded evaluators should investigate, (b) building a tool that would be useful for embedded evaluators and running it on suitable proxy data, and/or (c) writing a report based on mock findings.
Your Privacy and Fairness in Our Recruitment Process: We are committed to protecting your data, ensuring fairness, and adhering to workplace fairness principles in our recruitment process. To enhance hiring efficiency, we use AI-powered tools to assist with tasks such as resume screening. These tools are designed and deployed in compliance with internationally recognized AI governance frameworks. Your personal data is handled securely and transparently. We adopt a human-centred approach: all resumes are screened by a human and final hiring decisions are made by our team. If you have questions about how your data is processed or wish to report concerns about fairness, please contact us at info@apolloresearch.ai.
Location: Москва
В команду AIFA ищем QA-инженера, который будет отвечать как за классическое качество программного продукта, так и за оценку результатов работы LLM и финансового агента.
Роль подойдёт технически сильному специалисту или QA-инженеру, который хочет развиваться в автоматизации тестирования AI-продуктов.
Обязанности
* проводить функциональное, интеграционное, регрессионное и end-to-end тестирование AIFA
* тестировать backend API, пользовательский интерфейс и взаимодействие микросервисов
* автоматизировать API- и UI-тесты
* проверять длительные и параллельные процессы, стриминг, повторные вызовы и восстановление после ошибок
* создавать и поддерживать тестовые наборы для извлечения данных, Q&A, финансового анализа и моделирования
* формировать бенчмарки и метрики качества LLM-компонентов
* проверять воспроизводимость результатов и анализировать причины деградации качества
* участвовать в разборе дефектов и контролировать их исправление.
* Формировать quality gates для выпуска релизов
* организовывать валидацию результатов совместно с финансовыми экспертами.
Требования
* опыт в роли QA от 2х лет
* понимание основных видов и методик тестирования
* опыт тестирования REST API
* базовые знания Python и готовность развиваться в автоматизации
* базовый SQL
* умение работать с логами и локализовывать источник ошибки
* понимание клиент-серверной и микросервисной архитектуры
* внимательность к деталям и способность системно описывать дефекты
* опыт с pytest, CI/CD, Docker, нагрузочным тестированием или оценкой LLM будет преимуществом
* глубокая финансовая экспертиза не обязательна — необходимую предметную часть поможет освоить команда.
Условия
* комфортный современный офис рядом с м. Ленинский проспект
* гибридный формат работы
* ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования)
* корпоративный спортзал и зоны отдыха
* более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
* программа адаптации и помощь руководителя на старте (для вакансий уровня Junior)
* расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа
* гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
* подписка Прайм с возможностью совместного использования на трёх близких
* вознаграждение за рекомендацию друзей в команду Сбера.
Москва
San Francisco, CA • New York, NY • United States
УдалённоseniorIndonesia; Nigeria; Turkey; United States
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