Вакансии

Location: Intellias Meet your recruiter Carmen Beck carmen.beck@intellias.com https://www.linkedin.com... Vacancy details Software Engineering Fullstack AI Product Engineer Middle United States Office APPLY NOW REFER A FRIEND See the impact you make as an Applied AI Software Engineer delivering production‑ready solutions from day one. What project we have for you Our client is seeking an Applied AI Software Engineer to design, build, and deliver internal tools that improve the day-to-day effectiveness of engineering teams across requirements, validation, and UX/UI functions. The engineer will develop production-ready, AI-enabled applications that integrate existing models, LLM APIs, and AI services into practical business workflows. Typical solutions may include tools that generate engineering reports from structured inputs and prompts, or video-analysis workflows that identify activities in uploaded video, capture time-stamped events, and produce concise summaries. This is an execution-focused software engineering role, not an AI/ML research or model-development position. The successful candidate will use technologies such as Python, JavaScript/React, and AWS services to build reliable end-to-end pipelines, user-facing applications, and integrations that meet enterprise quality, security, and usability expectations. Working closely with engineers and cross-functional stakeholders, the candidate will help turn operational needs into maintainable AI-enabled tools and deliver them through established development practices. This is a full-time, fully onsite position in Raymond, Ohio, performed five days per week during standard business hours. What you will do Independently engage with requirements, validation, UX/UI, and other engineering stakeholders to understand current workflows, pain points, process gaps, and opportunities for automation or AI-enabled improvement. Elicit and clarify ambiguous business needs; translate them into practical problem statements, user journeys, functional requirements, acceptance criteria, technical designs, and incremental delivery plans. Assess solution options and independently recommend appropriate architecture, AI services, cloud platforms, frameworks, and implementation approaches based on user value, technical feasibility, security, maintainability, cost, delivery timeline, and the existing engineering environment. Design, develop, test, deploy, and maintain internal AI-enabled software tools that improve engineering productivity and operational workflows. Build end-to-end applications and pipelines that process engineering artifacts and data—including documents, spreadsheets, structured data, images, and video and produce useful outputs such as reports, summaries, classifications, etc. Integrate and orchestrate existing AI capabilities, including LLM APIs, managed AI services, computer-vision tools, and supporting libraries. This role focuses on applying existing models and services rather than training or developing foundational AI/ML models. Develop maintainable backend services, APIs, data-processing logic, and automation primarily in Python; contribute to JavaScript/TypeScript and React-based user interfaces where needed. Create prototypes or proof-of-concepts when useful to validate technical feasibility and user value, then evolve validated concepts into secure, reliable, supportable production solutions. Establish appropriate AI-output evaluation and validation methods, including test cases, structured output controls, error handling, observability, logging, and human review where the workflow requires it. Collaborate closely with cross-functional teams throughout discovery, implementation, testing, rollout, and continuous improvement; communicate scope, decisions, trade-offs, status, risks, dependencies, and technical limitations clearly. Participate in technical design reviews, code reviews, testing, troubleshooting, release activities, and ongoing support; maintain clear technical documentation, user guidance, and required project records. Perform assigned duties independently and in a timely, accurate, and professional manner. Adhere to organizational policies, procedures, security expectations, and applicable quality and safety requirements. What you need for this Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, a related technical field, or equivalent practical experience. Two or more years of professional experience in software engineering, including building, delivering, and maintaining production-quality applications, services, or internal tools. Strong proficiency in Python, including writing clean, maintainable, testable code and debugging software issues. Hands-on experience integrating existing AI capabilities into software solutions, such as LLM APIs, managed AI platforms, computer-vision services, or AI libraries. Experience building backend services, APIs, data-processing workflows, automation, or system integrations. Experience developing and deploying cloud-based applications using AWS, Azure, GCP, or similar platforms. Ability to evaluate technical options and recommend practical tools, frameworks, and architecture approaches based on user needs, security, maintainability, delivery timeline, and existing team capabilities. Ability to work effectively within established architecture, coding standards, version-control practices, and software-development processes with minimal onboarding. Experience collaborating with engineering and non-engineering stakeholders to translate operational needs into practical technical solutions. Strong written and verbal communication skills, including the ability to document technical decisions, communicate trade-offs, and clearly report delivery status, risks, and dependencies. Ability to work full-time, onsite in Raymond, Ohio, five days per week during standard business hours. Preferred Qualifications Experience with AWS services; the current team primarily uses AWS, with services such as S3, Lambda, EC2, Bedrock, IAM, CloudWatch, and API Gateway potentially relevant depending on the solution. Experience with JavaScript or TypeScript and React for internal web applications. Experience applying generative AI to business or engineering workflows. Familiarity with prompt engineering, structured outputs, model evaluation, retrieval-augmented generation (RAG), and validation methods for AI-generated results. Experience working with enterprise engineering artifacts and data sources, such as Excel files, documents, video, databases, or structured and unstructured data. Familiarity with Docker, CI/CD pipelines, automated testing, infrastructure-as-code, application monitoring, and production deployment practices. Familiarity with secure development, identity and access management, data privacy, logging, and responsible-AI practices. Experience working in agile or another structured enterprise software-development environment. What it’s like to work at Intellias At Intellias, where technology takes center stage, people always come before processes. By creating a comfortable atmosphere in our team, we empower individuals to unlock their true potential and achieve extraordinary results. That’s why we offer a range of benefits that support your well-being and charge your professional growth. We are committed to fostering equity, diversity, and inclusion as an equal opportunity employer. All applicants will be considered for employment without discrimination based on race, color, religion, age, gender, nationality, disability, sexual orientation, gender identity or expression, veteran status, or any other characteristic protected by applicable law. We welcome and celebrate the uniqueness of every individual. Join Intellias for a career where your perspectives and contributions are vital to our shared success. Skills AI AWS Python

Built is looking for an Innovation Software Engineer to build Marketplace software, prototypes, AI-powered workflows, and automation while learning from customer feedback.

Location: United States, Aliso Viejo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Agentic & AI Engineering Design, build, and operate production-quality agentic applications using agentic SDKs/harnesses — including multi-agent orchestration, subagent delegation, tool integration, and lifecycle hooks. Design Model Context Protocol (MCP) tool and resource interfaces that give coding agents/harnesses safe, reliable access to backend systems and enterprise data. Engineer prompts for reliable structured output (JSON schemas, few-shot examples, validation/retry loops) and build evaluation frameworks to measure and improve output quality. Manage context effectively across long documents, multi-turn conversations, and multi-agent handoffs; design escalation and human-in-the-loop patterns for production reliability. Developer Productivity Configure and extend Codex/Claude Code for team-wide use: AGENTS.md/CLAUDE.md hierarchies, custom slash commands, Agent Skills, path-specific rules, and plan mode. Integrate agentic development into CI/CD pipelines for automated code review, test generation, and PR feedback, tuned to minimize false positives and duplicate findings. Build and maintain MCP server integrations (project- and user-scoped) that extend agent-native development capabilities across engineering workflows. Identify high-value opportunities for AI-assisted development and design reusable capabilities that multiple teams can adopt, not just one-off solutions. Discovery, Prototyping & Production Delivery Partner directly with engineering teams to understand workflows, pain points, and opportunities through hands-on discovery. Rapidly prototype and validate new AI capabilities with real users, then take successful prototypes into secure, observable, maintainable production systems. Own the full lifecycle: implementation, testing, deployment, monitoring, and iteration. Technical Leadership Provide hands-on technical leadership through architecture discussions, code reviews, and troubleshooting of agentic systems. Mentor engineers on agentic design patterns, prompt engineering, and agent-native development practices. Communicate tradeoffs, risks, and results clearly to both technical and non-technical stakeholders. Contribute to engineering standards, reusable patterns, and documentation that help other teams build effectively with agentic development tools. Requirements 6+ years of professional software engineering experience, including significant hands-on work building and operating AI/LLM-powered or agentic applications. Strong programming skills (Java, Python, Go, Rust, or C++) and solid engineering fundamentals — API design, testing, debugging, code review, maintainable code. Practical, production-grade experience with agentic SDKs/harnesses, MCP, and LLMs — tool use, orchestration, RAG, context management, structured output, and evaluation. Experience designing MCP tool/resource interfaces and reasoning about tool selection, error handling, and reliability in multi-agent systems. Demonstrated experience integrating AI into CI/CD and developer workflows. Ability to work in ambiguous problem spaces, evaluate tradeoffs, and make pragmatic engineering decisions. Strong written and verbal communication skills, with experience mentoring and leading through influence. Build and maintain an engineering knowledge base for agentic workflows, including content ingestion, organization, updates, and retrieval. Connect it to agents through RAG and MCP so they can use trusted, current information with source citations. Preferred Qualifications Demonstrated expertise across agentic architecture, MCP integration, Codex/Claude Code configuration, prompt engineering, and context management. Experience building multi-agent research or customer support systems, or structured data extraction pipelines. Experience with AWS, Docker, Kubernetes, Terraform, and GitOps in support of AI/agentic infrastructure. Familiarity with vector databases, embeddings, and AI evaluation frameworks. Contributions to open-source projects involving AI, agentic systems, or developer tooling. Strong systems thinking — understands how models, agents, tools, context, APIs, data, and infrastructure fit together as production systems, and can reason about dependencies and tradeoffs across the stack. A track record of adapting quickly to new AI tools, models, and frameworks as the space evolves. Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice (where applicable) for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Основной фокус роли — разработка GenAI/LLM/Agentic‑сценариев для медицинского помощника.

Задачи: — Формировать стратегию развития клиентских ИИ-продуктов и создавать новое продуктовое направление с нуля — Исследовать потребности предпринимателей, выявлять перспективные сценарии применения ИИ и находить возможности монетизации — Формировать продуктовый портфель и roadmap развития AI-решений — Быстро проверять гипотезы с помощью LLM, no-code-инструментов, прототипов и MVP в циклах по 2–4 недели — Организовывать пилотные запуски с реальными клиентами, оценивать спрос и подтверждать готовность пользователей платить — Руководить продуктовыми командами, управлять бэклогом, приоритизацией и релизами — Совместно с инженерами развивать решения на базе LLM, RAG и промпт-инжиниринга — Выстраивать систему оценки качества ИИ-продуктов, включая A/B-тестирование, экспертные проверки и оценку точности ответов — Отвечать за юнит-экономику, монетизацию, конверсию в оплату, удержание и окупаемость продуктов — Разрабатывать модели монетизации: подписки, оплата за использование, дополнительные платные возможности — Обеспечивать вывод ИИ-продуктов на рынок через веб-сервис, мобильное приложение и партнёрские каналы Условия: — Доход обсуждается индивидуально, компания готова подстраиваться под финансовые ожидания кандидата — Оклад и премия по KPI — Формат работы обсуждается индивидуально — Официальное трудоустройство по бессрочному трудовому договору — График 5/2, оплачиваемый отпуск 28 календарных дней — Возможность с нуля создать и возглавить направление клиентских ИИ-продуктов — Доступ к существующей базе из десятков тысяч предпринимателей для исследований, тестирования гипотез и пилотных запусков — Реальное влияние на продуктовую стратегию и развитие технологического бизнеса — Возможность создавать продукты на стыке генеративного ИИ, финтеха и B2B SaaS Требования: — Опыт управления цифровыми продуктами от 5 лет, включая руководство продуктовым направлением или несколькими командами — Обязательный практический опыт запуска коммерческих продуктов на базе генеративного ИИ для внешних пользователей — Наличие реализованных AI-продуктов с подтверждёнными продажами и измеримыми бизнес-результатами — Глубокое понимание LLM, промпт- и контекст-инжиниринга, RAG, ограничений и особенностей генеративных моделей — Опыт работы с API OpenAI, Anthropic, YandexGPT, GigaChat или аналогичными решениями — Знание подходов к оценке качества ИИ: golden set, LLM-as-a-judge, экспертная оценка, A/B-тестирование — Умение управлять юнит-экономикой продукта и анализировать конверсию, удержание, LTV/CAC и окупаемость — Уверенное владение SQL, BI-инструментами и системами продуктовой аналитики — Опыт вывода продуктов на рынок, проверки гипотез и масштабирования успешных решений — Преимуществом будет опыт работы в финтехе, B2B SaaS, бухгалтерских или юридических сервисах — Опыт создания ИИ-агентов, интеллектуальных ассистентов и мобильных продуктов будет плюсом — Предпринимательское мышление, высокая самостоятельность и ориентация на коммерческий результат

• От 4 лет коммерческой разработки, из них не менее 2 лет на Go. • Go: HTTP и gRPC API, конкурентность, тестирование.

Location: Bangalore Workplace: OnSite LIFE AT UIPATH The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power. To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose. Could that be you? ABOUT THE ROLE Join the Vertical Solutions team and build UiPath's most ambitious product - an AI agentic orchestration platform that's been recognized as our Invention of the Year for two consecutive years. As a Senior Software Engineer, you'll be at the forefront of our Act 2 strategy, building the infrastructure that allows enterprises to seamlessly orchestrate AI agents, robots, and human-in-the-loop workflows to achieve critical business outcomes. You'll be working with Lax and the Maestro backend team to build the core orchestration engine that powers enterprise AI automation. This is a high-visibility, high-impact role on UiPath's biggest strategic bet. What You'll Do - Build and Scale: Design, develop, and maintain full stack for Vertical Solutions products leveraging AI Coding Assistants. - Hands-On Development: Write production-quality code daily, leveraging AI tools (Claude, GitHub Copilot, etc.) to enhance your development workflow - Prototype and Ship: Take ideas from Prototype to validate with real customers and turn the ones that prove value into production systems. - Measure what matters: Design evaluations, measure quality against real customer data, and understand when metrics mislead. Our systems are often non-deterministic. Responsible shipping means measuring honestly, not chasing vanity numbers. - Customer-Centric Engineering: Deeply understand who will use the features you build and why they need them, translating customer needs into elegant technical solutions - Ensure Reliability: Contribute to building highly scalable, reliable distributed systems that enterprises depend on. What We're Looking For: - Builder mindset — you enjoy turning ideas into working systems and taking ownership from Concept through, Customer impact and Production - Strong full stack knowledge including frontend systems like React and backend systems -Python and/or C# — most Vertical Solutions product development is Python (agents, APIs, ETL), while core platform work includes C#, frontend in React. Willingness to work across both is important. - Experience building production AI systems — LLMs, tool-calling, multi-agent architectures, orchestration frameworks (LangGraph, LangChain, or equivalent), structured outputs, orchestration, and evaluation of model behavior in real-world workflows - Distributed systems experience — designing resilient systems with idempotency, replay ability, state management, and long-running jobs - Strong analytical thinking — able to reason quantitatively about system quality and make sound decisions using imperfect signals - Comfortable with ambiguity and rapid prototyping — able to move from idea to proof-of-concept quickly and iterate based on customer feedback. - Experience with healthcare Tech/ Finance Tech/ Procurement Tech systems experience will be a big plus. What You'll Bring to the Team - Bachelor's/Master's degree in Engineering, Computer Science or equivalent experience. - 7+ years of software engineering experience, with 4+ years focused on distributed systems and backend architecture. - Strong proficiency in one or more system-level languages – Javascript / C# / Java etc - Full-stack experience: ability to work across backend services and frontend layers (REST/GraphQL APIs, basic UI integration, component contracts). - Deep understanding of object-oriented programming, architectural design patterns, system design, and data structures & algorithms. - Experience with React, TypeScript, or other modern frontend frameworks for deeper full-stack contribution. - Strong grasp of multithreading, asynchronous programming, synchronization, and cloud-native programming models. - Hands-on experience with cloud ecosystems: Azure, AWS, or GCP. - Proficiency with containerization and orchestration: Docker, Kubernetes, or equivalent. - Hands-on experience with AI coding tools and coding agents (e.g., GitHub Copilot, Cursor, Claude Code, or similar) and a demonstrated ability to integrate these into daily engineering workflows. - Experience driving team adoption of AI-powered productivity tools – setting norms, measuring impact, and iterating on usage patterns. - Familiarity with modern engineering practices: agile development, CI/CD, DevOps, and infrastructure as code. - Excellent verbal and written communication skills; proven success collaborating with globally distributed teams and managing complex, time-bound deliverables. - Ability to understand, communicate, and drive complex technical decisions with stakeholders at all levels. Nice to Have - Experience with healthcare Tech/ Finance Tech/ Procurement Tech systems experience will be a big plus. - Data science and evaluation - Experience with applied ML techniques such as classification, anomaly detection, ranking, or predictive modeling - Experience evaluating AI systems using experimentation, metrics, and empirical analysis to improve quality and reliability - Data and retrieval systems - Experience with large-scale data platforms (Snowflake, columnar warehouses, denormalized data models) - Familiarity with retrieval-heavy architectures, RAG systems, or citation-grounded AI workflows - Engineering for trustworthy AI - Experience blending deterministic and probabilistic systems (rules engines + AI) - Experience designing eval-driven systems, regression testing for LLM outputs, or human-in-the-loop review workflows - Platform and product development · Frontend familiarity (React, TypeScript) · Workflow orchestration platforms (Temporal, Airflow, Maestro, BPMN, Step Functions) · Kubernetes and distributed infrastructure · Experience in startups, applied research, or 0→1 product environments · Open-source contributions How We Work Vertical Solutions operates like an internal startup inside UiPath: small teams, fast iteration, and real customers in the loop. We build quickly, test ideas with users, and turn the best ones into products. Some ideas won’t make it — that’s expected. You’ll work in short cycles, demo frequently, and adapt as we learn. We care more about solving the right problem than protecting a plan that no longer fits. If you enjoy ambiguity, rapid feedback, and building where product boundaries move fast, you’ll likely thrive here. Why Join Us - Work on cutting-edge AI technology that's shaping the future of enterprise automation - Be part of a team building Times top 100 Invention of the Year (2 years running) - Collaborate with talented engineers who value rapid iteration and customer impact - Contribute to UiPath's Act 2 strategy - our most important product initiative. Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned. Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected. We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.

Задачи: — Проектировать и развивать runtime для работы с LLM и AI-агентами, участвовать в проектировании собственного orchestration / harness layer вокруг LLM; — Управлять контекстом модели и историей диалогов; — Разрабатывать agent loop и управлять жизненным циклом агентных сценариев; — Проектировать инструменты для агентов и интеграции с корпоративными системами; — Обеспечивать контроль доступа, согласованность состояния и обработку ошибок удалённых операций; — Развивать RAG и интеграцию корпоративных данных в LLM-приложения; — Работать со structured output, развивать потоковые диалоги (streaming), обеспечивать хранение истории диалогов и сохранение состояния; — Развивать наблюдаемость AI-вызовов, диагностировать и улучшать поведение LLM и агентов. — Развивать архитектуру модульного backend-приложения, REST API и бизнес-логику, включая валидацию, обработку ошибок и документацию; — Проектировать модели данных и миграции, оптимизировать запросы и кеширование; — Развивать аутентификацию, авторизацию и ролевую модель; контролировать доступ к внешним данным и управлять подключениями; — Программно управлять контейнерными средами: от создания и ожидания готовности до обработки сбоев и освобождения ресурсов; — Писать тесты, диагностировать production-проблемы, развивать наблюдаемость, согласовывать API с frontend-разработчиками. Требования: — Опыт backend-разработки от четырёх лет; — Практический опыт создания LLM-приложений; — Опыт работы с Java и backend; — Опыт промпт инжиниринга или простого подключения ChatGPT / OpenAI API недостаточен.

созданием пула LLM-агентов (Product Designer Agent, Architect Agent, QA Agent, Ops Agent).

Responsibilities: — Design prompts, agent logic and tools including function calling — Write test scenarios to evaluate the quality of agents — Analyze real agent conversations to identify and fix failures — Integrate agents with backend systems alongside the development team Requirements: — Minimum 2 years experience with Python — Experience building at least one large language model (LLM) agent or chatbot using APIs such as Gemini, OpenAI, or Claude — Strong skills in prompt engineering — Experience with function calling and Retrieval-Augmented Generation (RAG) — Proficiency in English Nice to have: experience with voice agents, multi-agent systems, evaluation tools like Langfuse or promptfoo, logistics domain knowledge, and knowledge of Uzbek or Russian languages. Benefits: — Salary starting from $1,500 per month — Office-based work in Tashkent To apply, send your CV to hr@gl-solutions.com with the email subject "AI Agent Engineer". Applications without a CV will not be considered.

Будущий сотрудник возглавит SEO-направление: сформирует сильную команду, выстроит масштабируемые процессы и будет отвечать за рост органического трафика клиентов. Твои задачи:

Translate business needs into functional AI use cases and automated tools. Integrate models via APIs and develop retrieval-augmented generation workflows.

etoro is looking for a BizOps AI Developer to build and deploy AI agents, RAG pipelines, and operational applications.

Responsibilities: — Design the architecture of AI agents including models, tools, and integrations — Establish standards for prompts, evaluations, and releases; review the team’s work — Decide when a fine-tuned model is ready for production — Hire and mentor ML and agent engineers Requirements: — Minimum 5 years experience in software or machine learning, with at least 2 years building large language model (LLM) systems — Delivered at least one LLM agent or chatbot to real users — Strong proficiency in Python — Experience with prompt engineering, function calling, retrieval-augmented generation (RAG), evaluations, and fine-tuning — Good command of English Nice to have: — Experience with voice agents, multi-agent systems, Google Cloud / Vertex AI, and logistics domain Benefits: — Salary from $3,000 per month — Office location in Tashkent Applications without a CV will not be considered. Email subject should be “AI Lead”.

Задачи: — Проводить security review AI/LLM-решений: LLM-приложений, AI-агентов, RAG, векторных БД, интеграций с внешними API и облачными LLM; — Участвовать в threat modeling AI-решений: prompt injection, jailbreak, утечки данных, небезопасные tool calls, избыточные привилегии AI-агента, RAG/data poisoning; — Проверять наличие и корректность защитных механизмов: guardrails, фильтры персональных данных, ограничения длины prompt/response, rate limiting, валидация ответов, контроль вызовов tools; — Оценивать безопасность работы с данными: персональные данные, конфиденциальная информация, источники данных для RAG, embeddings, индексы векторных БД; — Проверять, что AI-агенты работают по принципу минимально необходимых привилегий и не выполняют чувствительные операции без ручного подтверждения; — Проверять изоляцию пользовательских сессий, контекстов и памяти AI-решений; — Участвовать в проверке безопасности локального запуска LLM в Kubernetes: контейнеры, RBAC, secrets, network policies, ingress, resource limits; — Формировать требования к логированию, аудиту и трассировке AI-решений: trace ID, логи prompt/response, вызовы модели, вызовы tools, действия AI-агента; — Разрабатывать тестовые сценарии для проверки AI-решений на prompt injection, утечки данных, обход ограничений и небезопасное поведение агента; — Помогать командам разработки и эксплуатации безопасно использовать локальные и облачные LLM. Требования: — Опыт в кибербезопасности от 2–3 лет в одной или нескольких областях: Application Security, DevSecOps, Cloud Security, Kubernetes Security, API Security, Product Security; — Понимание принципов security review, threat modeling и безопасной разработки; — Понимание web/API-безопасности: аутентификация, авторизация, OAuth2/OIDC, SAML, JWT, RBAC, service-to-service-взаимодействие; — Базовое понимание AI/LLM-стека: LLM, prompt, system prompt, context window, embeddings, RAG, vector database, AI-agent, agent memory, tools/function calling; — Понимание основных рисков LLM-приложений: prompt injection, indirect prompt injection, jailbreak, утечка чувствительных данных, раскрытие system prompt, небезопасная обработка ответа модели, excessive agency; — Понимание особенностей безопасности RAG и векторных БД: например, Milvus, Qdrant, Weaviate, pgvector, Chroma, Elasticsearch/OpenSearch vector search; — Понимание рисков работы с персональными и конфиденциальными данными при использовании локальных и облачных LLM; — Базовое понимание Kubernetes и контейнерной безопасности: secrets, service account, RBAC, network policy, resource limits; — Умение формулировать понятные и проверяемые требования безопасности для продуктовых команд. Что мы ищем в кандидатах: — Опыт security review AI/LLM, RAG, чат-ботов, AI-ассистентов или агентских решений; — Знакомство с OWASP Top 10 for LLM Applications, OWASP Agentic AI Threats, MITRE ATLAS, NIST AI RMF; — Понимание безопасности agent tools/function calling: allowlist tools, схемы входных параметров, контроль прав, human-in-the-loop; — Опыт работы с SIEM/security logging: проектирование событий безопасности, аудит действий, расследование инцидентов; — Понимание подходов к безопасному исполнению кода, сгенерированного моделью: sandbox, изоляция контейнеров, запрет доступа к secrets, ограничения сети и ресурсов; — Базовые навыки Python, работы с JSON/YAML, API-тестирования или автоматизации security checks. Будет плюсом: — Опыт с OpenAI/Azure OpenAI, AWS Bedrock, Google Vertex AI, Anthropic или другими LLM-провайдерами; — Опыт с локальными open-source LLM и inference-сервисами; — Опыт настройки или проверки guardrails, фильтров персональных данных, DLP-подходов, content moderation; — Опыт участия в AI red teaming или разработке тестов на prompt injection и data leakage. Условия: — Формат: Гибридный (от 2-х дней в неделю, м. Технопарк); — Бесплатный доступ к телемедицине и очным приемам в частных клиниках (включая стоматологию и сессии с психологами); — Условия ипотечного кредитования от Сбербанка; — Индивидуальный план развития; — Английский язык с корпоративным преподавателем и скидки на курсы в Skyeng, компенсация обучения от ведущих платформ; — Официальное оформление, стабильные выплаты, оплата больничного и отпуска, современная техника; — Частичная компенсация спортивного абонемента, бесплатные занятия сквошем и футболом.

Location: Москва Наша команда [GigaLegal](https://sberpravo.ru/gigalegal/) создает автоматизированные решения для юристов с использованием технологий искусственного интеллекта (GigaChat и др.) Присоединяйся к нашей команде в качестве системного аналитика. Обязанности ### **Чем предстоит заниматься:** * собирать, анализировать и документировать требования от внутренних и внешних заказчиков в Confluence * описывать методы для интеграций, разрабатывать функциональные спецификации и API-контракты совместно с ML- и backend-командами * детализировать требования к функциональности ИИ-агентов (RAG-пайплайны, пайплайны для юридического анализа документов) * актуализировать существующую документацию * сопровождать проект от идеи до передачи заказчику готового продукта * формировать задачи на команды разработки * проводить демонстрации реализованного функционала. Требования ### **Что ожидаем от кандидата:** * высшее образование * опыт работы от 2-х лет в должности системного аналитика (плюсом будет опыт работы в консалтинге (банки/финтех/легалтех)) * понимание процесса разработки и жизненного цикла ПО * опыт работы в интеграционных проектах с использованием различных паттернов интеграций (REST, Kafka) * опыт работы с Jira, Confluence, Draw.io * опыт работы с базами данных, PostgreSQL, ElasticSearch (понимание структуры данных) * умение работать с инструментами проектирования API: Swagger, Insomnia * умение проектировать схемы процессов: UML-диаграммы, BPMN * понимание гибких методологий при разработке ПО _Будет плюсом:_ * понимание принципов работы LLM, RAG, LangChain / LangGraph * готовность разбираться в предметной области — российское законодательство, судебная практика, правовые вопросы; * навык работы с JSON-схемами, OpenAPI * базовые знания Python * опыт работы с PlantUML * навыки работы с генеративными AI-моделями Условия * формат работы офис на испытательном сроке, делее гибрид обсуждаем, локация офиса ул Вавилова д.19 * ежегодный пересмотр зарплаты, годовая премия * 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.

Location: San Francisco, California About Workato Workato is the leading Control and Execution Platform for Enterprise AI — the neutral platform enterprises trust to put AI to work across their business. Workato unifies data, applications, and processes into a single platform so AI can reliably orchestrate business processes in production at enterprise scale. Built on more than a decade of running mission-critical processes for over half the Fortune 500 — including Nasdaq, Amazon, Cisco, Vodafone, Atlassian, and Lucid Motors — Workato turns over 14,000 enterprise systems AI needs to act on into one governed execution layer. For more information, visit workato.com . Why join us? Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles . We are driven by innovation and looking for team players who want to actively build our company. But, we also believe in balancing productivity with self-care . That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives. If this sounds right up your alley, please submit an application. We look forward to getting to know you! Also, feel free to check out why: Business Insider named us an “enterprise startup to bet your career on” Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America Quartz ranked us the #1 best company for remote workers Responsibilities We're looking for an exceptional Senior Software Engineer to help build the distributed backend that powers our AI agent platform and the developer-facing products around it — the event-driven services, real-time integrations, and APIs that let agents reliably do real work. You'll be building the systems that need to stay correct and available on our path to 1M users over the next year. In this role, y ou will also be responsible to: Build event-driven, horizontally-scalable backend services that process work reliably and correctly even when parts of the system fail. Build real-time surfaces and integrations — streaming connections, gateways, and CLIs — that hold up under load. Integrate LLMs and agentic harnesses into production systems. Drive features end-to-end — from ideation and architecture through deployment, observability, and iteration. Raise the engineering bar through clean, well-tested code, thoughtful reviews, and mentorship. Requirements Qualifications / Experience / Technical Skills 5+ years shipping and operating production backend systems at scale. Strong proficiency in Python, and the judgment to write clean, well-tested, maintainable code under it. Deep distributed-systems fundamentals: you know how to keep systems correct and available under partial failure, backpressure, and load — and you design for it by default. Hands-on experience with event-driven, streaming, or real-time systems (queues, pub/sub, long-lived connections). Comfortable operating services in production on Kubernetes in the cloud — and instrumenting them with metrics, tracing, and dashboards so you can debug what you ship. Solid API and software-architecture instincts; you make and defend sensible trade-offs in ambiguity. LLM/agentic and developer-facing product experience (MCP, RAG, APIs, SDKs, CLIs) a strong plus. Our stack: Python, FastAPI, Postgres, Kubernetes, AWS. You don't need prior experience with all of it — we care that you can pick it up fast. Soft Skills / Personal Characteristics High agency and ownership: You drive work end-to-end, from ambiguity to shipped and iterated, without waiting to be told. A reliability mindset: You design for failure, not just the happy path. Product-minded:  You care about the users using what you build, not just the system behind it. AI-native: You use modern AI tooling (e.g., Claude Code) in your daily workflow and stay at the cutting edge of what it can do. Excellent written communication: We work async and write things down. (REQ ID: 3006)

Location: Mexico; Brazil; Costa Rica; Argentina; Colombia; Bolivia, Plurinational State of The Product Engineer will design, develop, and improve customer-facing features for a fast-growing digital marketplace. This role combines full-stack software development, product ownership, and problem-solving to deliver scalable solutions that enhance the user experience. The ideal candidate is a hands-on engineer who enjoys building products from concept to production, working independently, and using modern AI technologies to accelerate development. This position requires strong backend expertise in Python and Django, solid frontend development skills, and the ability to make practical technical decisions in a fast-paced startup environment. Responsibilities Design, build, and launch new product features from concept to production. Develop and maintain backend applications using Python, Django, and PostgreSQL. Build and improve responsive, user-friendly interfaces using JavaScript, HTML, CSS, and modern frontend technologies. Take ownership of the full development lifecycle, including architecture, implementation, testing, deployment, and maintenance. Integrate AI models, APIs, and automation tools into existing and new product features. Identify and resolve performance bottlenecks, optimize database queries, and improve application scalability. Maintain and improve existing systems by troubleshooting issues, refactoring code, and implementing technical improvements. Collaborate with product stakeholders to translate business requirements into functional, customer-facing solutions. Leverage AI-assisted development tools to improve coding efficiency while maintaining code quality. Work independently, prioritize effectively, and deliver high-quality solutions in a distributed startup environment. Requirements 3–6 years of professional experience in full-stack software development, preferably building SaaS platforms or customer-facing web applications. Strong hands-on experience with Python, Django, and PostgreSQL in production environments. Solid frontend development skills using JavaScript, HTML, CSS, and modern frameworks such as React. Demonstrated experience building and shipping complete product features independently. Experience developing and integrating REST APIs and third-party services. Practical experience integrating large language models (LLMs) or AI-powered functionality into applications. Strong understanding of database optimization, application performance, and scalable backend architecture. Experience using AI-assisted coding tools such as Claude Code, Cursor, or similar technologies. Previous experience working in startups, scale-ups, or small product-focused engineering teams. Strong problem-solving skills, technical ownership, and ability to work with minimal supervision. Advanced English communication skills (C1 or equivalent). Preferred Experience with React, Next.js, and TypeScript. Familiarity with OpenAI APIs, RAG, AI agents, and AI workflow automation. Experience with Redis, WebSockets, asynchronous processing, or real-time applications. Knowledge of AWS, Docker, CI/CD pipelines, and cloud infrastructure. Experience building or scaling SaaS products, marketplaces, or high-traffic platforms. Familiarity with payment integrations, third-party APIs, and workflow automation. Experience working with Figma or collaborating directly with product designers. Experience improving legacy systems, refactoring codebases, and optimizing database performance. Benefits Salary: $4,000 to $4,500 USD per month Performance Bonus — annual cash bonus tied to company growth (13th-month pay). PTO: 2 weeks Setup: Fully Remote