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Location: Metn, Lebanon About the Toters Toters is an on-demand e-commerce and delivery platform that enables customers to get anything in their city with the highest level of convenience. Technology is at the heart of everything we do. Our product and engineering teams work every day to build experiences that make customers’ lives easier while continuously improving internal systems to deliver faster and at the best cost. If you’re excited about working in a high-growth startup environment and want to be part of a team shaping the future of how people shop in the Middle East, we’d love to hear from you. About the Role We are looking for a Senior AI Backend Engineer to join Toters and help us build and scale the next generation of AI-powered products and engineering systems . This role sits at the intersection of Backend Engineering, AI Engineering, Platform Engineering, and Developer Enablement . We are looking for someone who not only builds AI-powered systems, but also understands how AI is adopted across an engineering organization and can help teams use AI effectively in their day-to-day development and product delivery. The ideal profile is similar to an Forward Deployed Engineer (FDE) : highly hands-on, comfortable working across different technical areas, able to understand ambiguous problems quickly, and capable of turning emerging AI capabilities into practical solutions. You will help define what good looks like for AI engineering at Toters , build reusable foundations, and enable engineering teams to adopt AI tools, agents, and AI-powered development practices. What You’ll Do Design and build backend systems and services powered by AI , integrating AI capabilities into production-grade products and internal platforms. Own and contribute to the AI engineering lifecycle , from experimentation and prototyping through deployment, observability, evaluation, and continuous improvement. Build and evolve AI-enabled developer and engineering platforms that improve productivity and accelerate software delivery. Lead the adoption of AI tools and workflows across engineering , helping teams identify high-value use cases and turn them into scalable solutions. Establish engineering standards and best practices around AI-powered development, agents, evaluation, observability, reliability, and productionization . Explore and implement emerging agentic engineering patterns , including agent-to-agent protocols, agent SDKs, tool calling, orchestration, and autonomous workflows. Build systems that leverage knowledge bases, knowledge graphs, retrieval, and contextual data to make AI applications more useful and reliable. Work closely with Backend, Platform, ML, Product, and Engineering leadership to identify opportunities where AI can meaningfully improve products and internal workflows. Prototype rapidly, validate ideas, and move successful experiments into reliable production systems. Develop reusable frameworks, libraries, and services that allow other engineers to build AI-powered applications without reinventing the foundations. Define and improve AI observability and evaluation practices, including monitoring quality, performance, reliability, cost, and model behavior. Stay current with rapidly evolving AI technologies and translate them into practical engineering solutions for Toters. What We’re Looking For 6+ years of experience software engineering , with a strong background in Backend Engineering, Platform Engineering, or a similar technical discipline. Strong experience building production-grade backend systems , preferably at significant scale. Strong programming skills in one or more backend languages such as Go, Java, or PHP . Hands-on experience building or integrating AI-powered systems and applications . Strong understanding of the AI application lifecycle , from experimentation to production deployment and monitoring. Experience with AI developer tools, LLMs, agents, agent SDKs, and AI-assisted software engineering workflows . Demonstrated experience leading AI adoption or enablement across an engineering team or organization. Ability to understand emerging AI technologies and distinguish between what is genuinely useful in production and what is experimental. Strong understanding of software architecture, distributed systems, APIs, and backend infrastructure . Experience with observability, reliability, monitoring, and production operations for complex systems. Strong problem-solving skills and the ability to work effectively in ambiguous, fast-moving environments. A builder mindset: you are comfortable going from "we should try this" → prototype → production . Nice to Have Experience working with AWS or other major cloud platforms. Experience with Platform Engineering or Developer Experience / Developer Enablement. Experience with MLOps or ML/AI infrastructure. Experience building AI agents and agentic workflows . Experience with Agent SDKs, agent-to-agent communication protocols, and orchestration frameworks . Experience with knowledge graphs, knowledge bases, RAG, or other approaches for grounding AI systems in company/domain knowledge . Experience building AI-powered developer tools or internal engineering platforms. Previous experience in an FDE, Solutions Engineer, Developer Experience, AI Platform, or similar highly cross-functional engineering role . Experience working with modern AI coding and development tools such as Claude or similar AI development platforms .

Задачи: — Проектировать, разрабатывать и оптимизировать графы знаний на базе Neo4j. — Разрабатывать решения Graph-RAG для задач поиска, извлечения информации и использования AI. — Проектировать модели графовых данных, связи между сущностями и общие модели данных. — Создавать и автоматизировать пайплайны для загрузки, трансформации и обработки данных. — Работать со структурированными и неструктурированными наборами данных, включая профилирование, сбор данных, валидацию и проверки качества. — Разрабатывать масштабируемые потоки обработки данных с использованием AWS-сервисов. — Работать с потоковыми данными и обработкой на базе Kafka. — Участвовать в развитии архитектуры, управляемой метаданными, каталогов данных и принципов Data Fabric. — Участвовать в автоматизации data pipelines и разработке пайплайнов на базе AI-агентов. Требования: — Сильный практический опыт работы с Neo4j, включая моделирование графовых данных и оптимизацию запросов. — Практический опыт проектирования и реализации решений Graph-RAG. — Сильные навыки разработки на Python. — Опыт работы со stream processing и Kafka. — Практический опыт работы с технологиями обработки данных в AWS, включая AWS Glue, Data Catalog, Data Lake/Lake Formation и связанные сервисы. — Глубокое понимание data pipelines, data modeling и data architecture. — Опыт обработки как структурированных, так и неструктурированных данных. Будет преимуществом: — Опыт работы с PostgreSQL. — Сильный опыт построения data pipelines на AWS. — Опыт работы с LangChain, CrewAI или аналогичными агентными фреймворками. — Опыт автоматизации data pipelines с использованием AI-агентов. — Знание распространенных моделей данных, metadata-driven processing и принципов Data Fabric. — Опыт интеграции Knowledge Graphs с решениями на базе RAG/LLM. Требования по доступности: — Возможность частично пересекаться с рабочими часами по тихоокеанскому времени США (US Pacific Time), включая доступность до 11:00 AM PT. Условия: — Возможности для профессионального и карьерного развития. — Поддержка в получении профессиональных сертификаций. — Программа менторства. — Медицинская страховка. — Участие в корпоративных мероприятиях. — Гибкие форматы работы (гибридный или удалённый). — Оплачиваемый отпуск и больничные.

Location: San Francisco; Toronto Workplace: OnSite Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit. ABOUT THE COMPANY Our client builds the data layer that AI agents run on. One API call turns any URL into clean, structured, LLM-ready data. It is already the default way a huge number of developers pull web data into their AI systems. The numbers back it up: 8 figures in ARR in year one, more than doubled that in year two, and 180,000+ GitHub stars, placing its open-source project among the top 50 repositories of all time. They just closed a $75M Series B. The company is small, moving fast, and hiring people who want to build the next chapter with them. THE MISSION They believe developers and AI agents should not have to fight the web to get useful data out of it. Every hour spent maintaining a scraper, dealing with stale pages, or working around brittle retrieval systems is an hour taken away from the actual product. Their job is to make that problem disappear: give AI systems reliable access to the live web, then make the results clean, current, structured, and useful enough to power real products. THE OPPORTUNITY As a Search Engineer, you will own ranking quality and relevance for an LLM-driven search and retrieval product. This is a role for an engineer whose primary, hands-on discipline is production search quality. You have personally shipped ranking or re-ranking changes, measured their impact, and can clearly describe the relevance, recall, conversion, or other search-quality metric you improved—including the result. You will work directly with the Head of Search and a small team across crawling, indexing, retrieval, and search serving. These systems are central to delivering excellent results at scale, but they are not substitutes for relevance ownership. Your role is to improve search quality while navigating the real constraints of web-scale retrieval: freshness, deduplication, latency, reliability, and cost per query. WHAT YOU’LL DO - Own ranking quality and relevance for LLM-driven retrieval - Design and build the crawling, indexing, and retrieval systems - Push down latency and cost per query while search volume grows - Own services end to end: design, ship, monitor, and iterate in production - Work directly with the Head of Search and the rest of the search team on the roadmap WHAT YOU BRING - 3+ years of experience building and operating search or retrieval systems in production, with ranking and relevance as your primary, owned discipline - A specific example of a ranking or re-ranking change you personally owned, the search-quality or business metric it moved, and the numerical impact achieved - Hands-on information-retrieval depth across BM25 and lexical retrieval, semantic/vector retrieval, hybrid retrieval, re-ranking, retrieval evaluation, or RAG evaluation - Experience measuring search quality through relevance, recall, conversion, CTR, NDCG, MRR, query satisfaction, or comparable production metrics - End-to-end ownership of search services: you have designed, shipped, monitored, debugged, measured, and iterated on production systems - Strong backend systems programming skills in Go, Rust, Python, or a comparable language. - Experience balancing relevance, latency, cost, correctness, and reliability under real production constraints - Comfort working through ambiguity, setting technical direction, and shipping quickly with a build-measure-iterate operating style KEY SUCCESS DRIVERS The people who do well here have personally owned search quality in production, think end-to-end about relevance, crawling, indexing, serving, latency, and cost, and thrive in ambiguity by shipping, measuring, and iterating quickly without needing a fully defined playbook. WHY JOIN? - Compensation & Equity: San Francisco: $235,000–$260,000 USD base salary, plus competitive equity. Toronto: $217,000–$233,000 CAD base salary, plus competitive equity. - Traction: 8 figures in ARR in year one, more than doubled in year two. 180,000+ GitHub stars and a developer base showing up before you even start selling to them. $75M Series B closed in 2026, backed by top-tier investors - Team: ~40 people total, real visibility with the founders and leadership. No layers, no committees, fast decisions, short feedback loops - Benefits: 100% employer-paid medical, dental, and vision (50% for spouse and kids); employer-paid life, short-term, and long-term disability insurance; 401(k), pre-tax FSA, and commuter benefits; pet insurance; 15+ days PTO; 12 weeks fully paid parental leave for moms and dads; $100/month wellness stipend; $1,000/year learning and development budget; 3-month paid sabbatical after 4 years; team offsites twice a year; SF HQ perks and a loaner e-bike for commuting - Visa: not open to visa sponsorship on this one (Candidates must be authorized to work in the United States or Canada). INTERVIEWING PROCESS 1. Intro Chat 2. Technical Chat 3. Founders Chat 4. Paid Work Trial (~40 hours) We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. Available Location: Toronto, Canada About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. We’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. What you will do as a Customer Engineer The Customer Engineer (CE) is the core driver of our technical go-to-market strategy: a trusted technical advisor and primary architect of the customer journey. You will bridge the gap between technical strategy and business value—guiding enterprise clients from initial pre-sales technical validation through onboarding, deployment architecture, and full lifecycle expansion. Sitting within the GTM organization and reporting to a Customer Engineering Leader, you will not hand off your customers once an initial agreement is reached. Instead, you will operate as a quota-carrying technologist, leveraging AI-augmented workflows to eliminate administrative toil so you can focus on high-value architectural design and driving measurable business outcomes across the entire customer journey. Key Responsibilities Technical Validation: Partner closely with Account Executives to lead technical deep-dive discovery, capture business requirements, and map complex customer infrastructure - DNS, CDN, Zero Trust, Network Security, Workers - to fit-for-purpose Cloudflare architectures and bespoke solutions. . Define, scope, success criteria, and technical evaluations plans for Proof of Concepts (PoCs) and Technical Validations. Deliver tailored technical presentations, architectural diagrams, and demonstrations that show how Cloudflare solves specific performance, security, and reliability challenges. Proactively address complex technical objections, security compliance questions, and edge-case architectural requirements during the sales cycle. Take accountability for a suitable solution deployment strategy (Customer, Partner or Cloudflare Professional services) being an integral part of all proposals. Customer Adoption & Value Realization: Provide oversight to technical onboarding and implementation, but not execute the implementation, serving as the primary executive and engineering contact for the customer. Design structured migration and onboarding blueprints tailored to the customer’s environment (e.g. DNS migrations, Zero Trust rollouts, WAF tuning guidance), and act as the lead consultant for customer engineering teams, walking them step-by-step through configuration best practices.  Partner with Account Executives to own discovery, demos, onboarding, technical health, risk, and expansion strategy. Proactively monitor customer health scores and telemetry to ensure rapid time-to-value, resolve integration bottlenecks, and reduce deployment risk. Commercial Accountability & Expansion: Carry a variable quota tied directly to new business acquisition and/or ongoing account growth. Be commercially accountable for ensuring deep platform adoption, retaining revenue, and identifying strategic cross-sell and up-sell opportunities based on product usage data. Lead technical Quarterly Business Reviews (QBRs) to translate platform capabilities into return on investment for C-level executives. Trusted Advisory: Act as a trusted technical advisor throughout the entire customer lifecycle, maintaining a continuous, deep relationship with key stakeholders from initial onboarding through maturity, renewal, and expansion. Provide thought partnership on architecture, AI control layers, security posture, and deployment confidence. Identify potential deployment risks or integration bottlenecks early, and provide remediation strategies to de-risk customer outcomes. AI Orchestration & Workflow Automation: Leverage AI agents, Large Language Models (LLMs), and internal platforms to automate routine tasks such as RFP/Security Questionnaire responses, sandbox provisioning, basic telemetry monitoring, and internal/external documentation, reclaiming your time for strategic customer advisory. Education & Enablement: Partner closely with the Enablement Team to design, build, and govern technical resources. Define, document, and educate both internal teams and customers on deliverables such as Standard Operating Procedures (SOPs), architectural best practices, and technical guides to continuously raise the technical baseline across the organization. Minimum Qualifications Experience: Experience in a customer-facing technical role, such as Solutions Engineering, Customer Engineering, Professional Services,  Sales Engineering, Technical Account Management, or as a Forward Deployed Engineer (years of experience required will vary based on Associate, Senior, Staff, or Principal leveling). Architectural Mindset: Ability to white-board, design, and articulate complex enterprise network and security architectures clearly. Consultative & Advisory Skills: Excellent communication skills with the ability to translate deeply technical concepts into business outcomes for both hands-on engineers and C-level executives. Commercial Mindset: Proven track record of operating in a quota-carrying or revenue-aligned environment, with a strong understanding of SaaS metrics, business value translation, and enterprise sales cycles. Communication: Exceptional presentation and stakeholder management skills, capable of bridging the gap between deep technical implementation details and high-level C-suite business strategy. Technical Breadth: We do not expect every candidate to be an expert in every domain. Qualified candidates will demonstrate depth in at least four of the technical areas below: Internet fundamentals: Deep understanding of how the Internet works, including OSI Model layers 1–7, BGP, GRE, TCP/UDP, DNS (authoritative and recursive), HTTP(S), and SSL/TLS. Security: Expertise in the security of Internet properties, including WAF, Bot Management, Firewalls, Rate Limiting, (M)TLS, Zero Trust, and SASE concepts. Performance: Expertise in the performance of Internet properties, including speed, latency, caching, video streaming, HTTP/2, and TLS 1.3. AI Proficiency: Familiarity with prompt engineering, AI-assisted scripting and log analysis, LLM utilization, and workflow automation to augment everyday CE workflows. Coding/Scripting: Proficiency in Python, JavaScript, Bash, Lua, Go, or similar languages to write custom integration scripts, API connectors, and edge computing functions. Developer Platform Fluency: Experience designing, building, deploying or scaling applications using RESTful/GraphQL APIs, SDKs, webhooks, and developer tooling in cloud-native environments. Familiarity with infrastructure-as-code (Terraform, Pulumi), CI/CD pipelines, and observability for developer-led deployments. Strongly Preferred Qualifications (The "Good-to-Haves") Technical Enablement: Track record of creating and delivering technical enablement - workshops, code samples, documentation, or developer onboarding - that accelerates customer adoption of complex platforms. Applied AI Knowledge: Experience with LLM orchestration, Retrieval-Augmented Generation (RAG) architectures, and model-access controls. Regulatory Knowledge: Understanding of regulatory requirements such as PCI DSS, HIPAA, and SOC 2. Hyperscaler / Digital Native Background: Talent coming out of hyperscalers, digital natives, distributed systems environments, or startups is strongly valued for its deeper cloud fluency and advanced architecture depth. Education Undergraduate or graduate degree in Computer Science, Engineering, or a related field. Travel This role will require travel up to 20–50% to attend customer meetings, conferences, industry events, and other in-person team meetings, within the assigned territory. For this reason, candidates must have reliable personal or local public transportation to complete all required travel. Required travel is reimbursable in accordance with the Company's Travel & Expense Policy, as it may be amended from time to time. Compensation This role features a competitive base salary and a variable compensation structure tied directly to the successful execution of full-lifecycle commercial targets, including new business acquisition, ongoing adoption milestones, and overall account expansion. What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Ключевое направление проекта — тестирование AI-систем, включая решения на базе RAG и LLM. Требования: — Гражданство и локация РФ — Опыт работы в QA от 5 лет — Опыт автоматизации тестирования от 3 лет — Хороший практический опыт автоматизации на Python — Обязателен опыт тестирования AI-систем, LLM и RAG — Технический стек / навыки: Python, Pytest, xdist, Playwright, CI/CD, Kafka, SQLAlchemy, Тестирование API Задачи: — Разработка и поддержка автотестов на Python — Написание и поддержка тестов на Pytest, параллельный запуск с xdist — Автоматизация UI-тестирования с Playwright — Интеграция автотестов в CI/CD, работа с Kafka и базами данных (SQLAlchemy) — Тестирование AI-систем, LLM-решений и RAG-пайплайнов; анализ результатов и выявление дефектов Условия: — удалённая работа — полная занятость — вилка до 146 000 ₽ на руки.

Задачи: — Развитие платформы: работать над функционалом, стабильностью и производительностью. — Развивать AI-функционал: LLM-based сценарии, tool calling, RAG, работу с контекстом, кэширование и другие механики. — Разбираться со сложными production-инцидентами и устранять не только последствия, но и причины проблем. — Клиентские внедрения: превращать пожелания клиента в дорожную карту запуска. — Проектировать архитектуру интеграции Sance.AI с инфраструктурой клиента. — Отвечать за техническую часть сложных клиентских запусков — от discovery до production. — Команда и инженерные практики: менторить junior/middle-разработчиков, помогать с декомпозицией задач, архитектурой и сложными техническими вопросами. — Проводить code review и повышать качество решений команды. Требования: — От 4 лет коммерческого опыта в разработке, от 1 года опыта в продуктовой команде. — Уверенные знания в asyncio, очередях, кешировании, конкурентности. — Практический опыт создания production-функционала на базе LLM, а не только использование ChatGPT. — Опыт с OpenAI API или другими LLM API. — Знания prompt engineering, tool calling, RAG, caching и context management. — Опыт с embeddings, vector search и agentic workflows. — Опыт тестирования и evals. — Понимание production-проблем: latency, стоимость, rate limits, hallucinations, retries и observability. — Уверенная работа с REST API сторонних сервисов, webhooks и внешними сервисами. — Умение разбираться в документации. — Опыт интеграций с CRM — особенно amoCRM и/или Bitrix24. — Умение довести размытую бизнес-задачу до работающего production-решения, видеть системные проблемы и помогать команде расти. — Будет плюсом опыт B2B/Enterprise-внедрений, highload и event-driven систем. — Собственные AI-проекты и опыт работы в стартапах. Условия: — Работа в быстрорастущем AI-стартапе, влияние на продукт, архитектуру и процессы. — Разнообразные задачи, крупные клиенты и короткий путь от идеи до production. — Быстрый карьерный рост.

Location: Hyderabad, Telangana, India About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: Hyderabad, India Experience Level: 8+ years Work Model: Hybrid, 3 days per week in office Employment Type: Full Time Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and hybrid: This role is based in Bengaluru or Hyderabad and requires working from the office three days per week. Candidates must currently be based in one of these two cities. Relocation assistance is not available. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. Strong retrieval depth: Experience building and improving production retrieval systems, with a practical understanding of embeddings, vector and hybrid search, reranking, evaluation, and diagnosing retrieval quality. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Location: Bengaluru, Karnataka, India About Turing Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com . Role: Forward-Deployed AI Engineer — Enterprise AI Location: Bengaluru, India Experience Level: 8+ years Work Model: Hybrid, 3 days per week in office Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you’ll define the frontier by building beyond it. You’ll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world’s leading enterprises. As a Forward-Deployed AI Engineer, you’ll own outcomes end to end—from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You’ll develop generative AI solutions in the real world, driving measurable impact and return on investment within large institutions. Enterprise AI is intense, intellectually challenging work. It won’t be for everyone, but it may be exactly the challenge you’re looking for. As a Forward-Deployed Engineer, You Will Find the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, challenge assumptions, and translate complex business needs into clear technical direction. This requires curiosity and business acumen as you discover business workflows and jointly define the outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems, from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Own the Outcome You won’t simply be given a list of responsibilities—you’ll have the authority to own the outcome for your client and make a real-world impact through your work. You’ll lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. You’ll work with clients who have uncompromising expectations for quality, making this a demanding environment—and an ideal proving ground for people who seek difficult, high-impact challenges. Client-first and hybrid: This role is based in Bengaluru or Hyderabad and requires working from the office three days per week. Candidates must currently be based in one of these two cities. Relocation assistance is not available. You’ll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you’ll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Deep production engineering experience: Typically 8+ years building and operating sophisticated software systems, with expertise in Python, backend systems, APIs, databases, distributed systems, system design, and cloud infrastructure. Hands-on agentic AI experience: Experience building production LLM and agent systems using orchestration, tool use, context engineering, memory and state, retrieval, and multistep workflows. Strong retrieval depth: Experience building and improving production retrieval systems, with a practical understanding of embeddings, vector and hybrid search, reranking, evaluation, and diagnosing retrieval quality. End-to-end systems ownership: A track record of taking complex systems from architecture through deployment and scale, with a practical understanding of evaluation, observability, reliability, security, guardrails, latency, scalability, and cost. Exceptional customer and technical leadership: The ability to enter unfamiliar environments, earn trust quickly, navigate ambiguity, challenge assumptions constructively, and communicate effectively with senior engineers and business executives. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace  and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here .

Задачи: — техническое лидерство в команде разработки и организация работы продуктовой команды; — реализация интеграций на техплатформе (PlatformEco, Gravitee); — реализация агентов на ИИ-платформе; — интеграция агентов в ИТ-ландшафт компании; — внедрение ИИ-компонентов в агентский портал; — формирование роадмапа, приоритизация бэклога и управление жизненным циклом продукта. Требования: — опыт технического руководства командой разработки на C# / .NET Core; — понимание принципов проектирования сервисов, код-ревью, поддержания стандартов разработки; — глубокое понимание Agile / Scrum / Kanban и опыт их адаптации под крупные организации (внедрение, оптимизация процессов); — навыки формирования роадмапа, приоритизации бэклога, управления жизненным циклом продукта; — понимание архитектуры корпоративных интеграций и API-менеджмента; — опыт проектирования и реализации интеграций между разнородными системами; — актуальное понимание Generative AI и LLM; — опыт с концепцией ИИ-агентов: архитектура, сценарии использования, ограничения и риски. Будет плюсом: — опыт разработки на скриптовых языках: node.js / python; — базовые знания RAG (Retrieval-Augmented Generation), векторных баз данных и промпт-инжиниринга. Условия: — полный рабочий день; — можно удалённо.

Требования: — 5+ лет в IT в целом, включая 2+ года практического опыта создания приложений, агентов и автоматизаций на базе LLM, применение генеративного ИИ в реальных продуктах и бизнес-задачах, подтверждённая старшинство в полном цикле решений. — Опыт разработки на Python: проектирование сервисов, работа с базами данных и API, написание тестов, уверенное владение Git, контейнерами и CI/CD. — Опыт работы с RAG и retrieval: embeddings, векторные базы данных, настройка качества поиска. — Не просто скрипты или расширение существующих автоматизаций. Компания создаёт SaaS-платформу для поддержки малого и среднего бизнеса в области налогов, финансов и бухгалтерии. Условия: — Полностью удалённая работа. — Найм по всей Европе с предпочтением кандидатов, работающих в часовом поясе CET (±3 часа).

Задачи: — анализировать бизнес-процессы, системы и потребности партнеров; — проектировать интеграции: REST API, Webhooks, event-driven; — описывать AS-IS / TO-BE, BPMN и UML; — формировать функциональные и нефункциональные требования; — участвовать в технических переговорах с партнерами; — выявлять архитектурные риски и контролировать реализацию; — готовить техническую документацию. Требования: — 2–3+ года опыта в системном анализе в IT; — опыт с REST API, Use Cases, User Stories, UML/BPMN; — понимание LLM, AI-агентов и RAG; — уверенный SQL и понимание клиент-серверной архитектуры; — умение находить общий язык с бизнесом, продуктом и разработкой. Условия: — работа из офиса Astana Hub; — график 5/2, 09:00–18:30; — условия обсуждаются индивидуально.

Задачи: — Разрабатывать AI-агентов на Python — Интегрировать модели и внешние API — Работать с RAG и Tool Calling — Упаковывать решения в Docker — Разворачивать через Helm в Kubernetes — Работать с ArgoCD и анализировать логи — Исправлять ошибки и самостоятельно обновлять production-деплои — Работать с SCA-сканерами и зависимостями Требования: — 3–6 лет опыта, Middle / Senior — Python + LangChain / LlamaIndex / Semantic Kernel или аналоги — Docker, Kubernetes, Helm — Bash, debugging, анализ логов — Понимание AI Agents, RAG, Tool Calling — Глубокое понимание Python-зависимостей (pip, poetry, virtualenv) — Высокая самостоятельность: от кода до запуска в production Условия: — Формат работы: Remote — Занятость: Full-time — Зарплата: до 260 000 ₽ на руки — Оформление: ИП / СМЗ — Локация: РФ, гражданство РФ

Задачи: — трансляция бизнес-потребностей в технические требования к функционалу и логике AI-агентов — проектирование интеграций: описание взаимодействия агентов с внешними API (входы/выходы, форматы данных, обработка ошибок, таймауты, retry-логика) — проектирование меж-агентского взаимодействия: оркестрация агентов, передача контекста, приоритизация запросов и сценарии эскалации — сопровождение до ПРОМ: совместно с промпт-разработчиками доводите требования до готовых промтов, контролируете соответствие промтов исходным бизнес-требованиям и передача системных требований в команду сопровождения — взаимодействие с заказчиками, менеджментом и командой разработки, обеспечение прозрачности процесса — исследование рынка и проверка гипотез: быстрая оценка применимости AI-решений под задачу, сравнение подходов (LLM, RAG, инструменты, мультиагентность), подготовка обоснованных рекомендаций Требования: — уверенный технический бэкграунд: понимание архитектуры веб-систем, REST API, gRPC, форматов данных (JSON, OpenAPI/Swagger, Protobuf), интеграционных паттернов (sync/async, webhooks, очереди) — понимание AI-концепций на уровне теории либо применения: как работают LLM, промпт-инжиниринг, ограничения и «галлюцинации»; RAG (retrieval-augmented generation), векторные БД; архитектура AI-агентов: инструменты (tools/function calling), оркестрация, мультиагентные сценарии; знакомство с LangGraph/LangChain или аналогичными фреймворками — понимание, что такое harness (core-платформа для GenAI-агентов) и его составляющих — умение проектировать логику агентов: сценарии, состояния, ветвления, обработка ошибок, fallback-сценарии — навыки декомпозиции задач и написания точных, проверяемых технических требований (User Story + критерии приёмки, или спецификации) — опыт взаимодействия с бизнесом и перевода требований в технические спецификации — опыт работы с PostgreSQL/SQL (чтение схем, описание маппинга данных) — умение быстро проверять гипотезы: исследовать рынок AI-решений, оценивать применимость технологии под задачу Будет плюсом: — понимание Java/React-стека на уровне общения с командой (что реально, а что нет в существующей архитектуре) — опыт в продуктовых командах, где аналитик сопровождает фичу от идеи до релиза — опыт написания технических заданий для промпт-разработчиков — базовые навыки прототипирования (Python/псевдокод/конфигурация) для быстрой проверки гипотез Условия: — комфортный современный офис — корпоративный спортзал и зоны отдыха — уникальная система обучения Сбера для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС и льготное страхование для семьи — 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.

Задачи: — Автоматизировать подготовку отчётов для заказчиков в Word и PowerPoint. — Разрабатывать и внедрять чат-ботов в MAX для автоматизации аналитических процессов: организовывать формирование и отправку файлов с учетом прав доступа пользователей, настраивать сбор данных с помощью парсинга и реализовывать ответы на вопросы по базе знаний с использованием RAG. — Выгружать и обрабатывать данные из ClickHouse. — Проверять полноту и корректность данных. Требования: — Опыт в разработке и внедрении чат-ботов для MAX или Telegram, создании и автоматизации аналитических отчётов или дашбордов будет плюсом. — Уверенное владение Python. — Уверенное владение SQL для создания баз данных под проекты. — Умение применять ИИ-инструменты для решения рабочих задач, в том числе создавать агентов и настраивать навыки (skills). — Будет плюсом: знание библиотек python-docx, python-docx-template и python-pptx. Условия: — Стабильная официальная заработная плата (уровень дохода обсуждается на собеседовании). — Оформление и социальные гарантии в соответствии с ТК РФ. — Доброжелательный, профессиональный коллектив. — Рабочий день с 9:30 до 18:15 (в пятницу до 17:00). — Возможность быть причастным и влиять на развитие медицинской науки. — Общественная значимость результатов работы.

Location: San Francisco NOTE ON ELIGIBILITY: this role is for industry candidates already working in software engineering for the past 1+ years. New grads and current students should NOT apply to this role (instead, visit pplx.ai/newgrads https://pplx.ai/newgrads). ABOUT THE ROLE In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, through Search, Comet, and Computer. Product Engineering owns those experiences end to end, from the interface a user touches to the search and model calls behind it, on top of roughly 200M queries a day and a 200B+ URL index. This is a full stack role in the truest sense. There are no frontend or backend lanes here, and no one waits for a ticket before starting. It suits people who love to build and want the room to do it. What you have shipped and how quickly you learn tell us far more than years on a resume or where you went to school. WHAT YOU WILL DO - Own a user-facing surface end to end, from the interaction, design, and frontend through the application logic, APIs, data models, and the search or model calls behind them. - Ship to production continuously. New engineers typically have code in front of users in their first week. - Build with AI as a primary tool, not a novelty. We expect you to use agents and coding models aggressively to move faster, and to have sound judgment about when their output is wrong. - Turn ambiguous product ideas into working prototypes, then use real usage data and evals to decide what survives. - Raise the quality bar on reliability, latency, and craft for the surfaces you own. - Work directly with designers, PMs, and research engineers, without unnecessary process in between. WHAT WE LOOK FOR - 1+ years of professional software engineering experience, or a track record of strong internships where you shipped production code at scale. - Strong in at least one backend language, such as Python or Go, with real experience across services, APIs, and relational data modeling. Comfortable working in React and TypeScript on the frontend. - Real evidence of building: production work you understand in depth, shipped side projects with actual users, meaningful open-source contributions, hackathon wins, or research you turned into working software. - Comfort with ambiguity and an instinct to start building incrementally rather than wait for a spec. - Hands-on experience with AI products, with opinions about their rough edges and what that means for the product you are building. NICE TO HAVE - Experience with our stack: React or Next.js, Python, Go, PostgreSQL, Redis, Docker, AWS. You will not be expected to know all of it on day one. - Experience building on top of LLMs: AI orchestration, RAG, evals, agents, tool use. - Product taste. You can tell a good interface from a bad one and explain how to improve it. - A public track record we can read, such as GitHub, a technical blog, or a demo we can try.

Location: San Francisco NOTE ON ELIGIBILITY: this role is for industry candidates already working in software engineering for the past 1+ years. New grads and current students should NOT apply to this role (instead, visit pplx.ai/newgrads https://pplx.ai/newgrads). ABOUT THE ROLE In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, through Search, Comet, and Computer. Product Engineering owns those experiences end to end, from the interface a user touches to the search and model calls behind it, on top of roughly 200M queries a day and a 200B+ URL index. This is a full stack role in the truest sense. There are no frontend or backend lanes here, and no one waits for a ticket before starting. It suits people who love to build and want the room to do it. What you have shipped and how quickly you learn tell us far more than years on a resume or where you went to school. WHAT YOU WILL DO - Own a user-facing surface end to end, from the interaction, design, and frontend through the application logic, APIs, data models, and the search or model calls behind them. - Ship to production continuously. New engineers typically have code in front of users in their first week. - Build with AI as a primary tool, not a novelty. We expect you to use agents and coding models aggressively to move faster, and to have sound judgment about when their output is wrong. - Turn ambiguous product ideas into working prototypes, then use real usage data and evals to decide what survives. - Raise the quality bar on reliability, latency, and craft for the surfaces you own. - Work directly with designers, PMs, and research engineers, without unnecessary process in between. WHAT WE LOOK FOR - 1+ years of professional software engineering experience, or a track record of strong internships where you shipped production code at scale. - Strong in at least one backend language, such as Python or Go, with real experience across services, APIs, and relational data modeling. Comfortable working in React and TypeScript on the frontend. - Real evidence of building: production work you understand in depth, shipped side projects with actual users, meaningful open-source contributions, hackathon wins, or research you turned into working software. - Comfort with ambiguity and an instinct to start building incrementally rather than wait for a spec. - Hands-on experience with AI products, with opinions about their rough edges and what that means for the product you are building. NICE TO HAVE - Experience with our stack: React or Next.js, Python, Go, PostgreSQL, Redis, Docker, AWS. You will not be expected to know all of it on day one. - Experience building on top of LLMs: AI orchestration, RAG, evals, agents, tool use. - Product taste. You can tell a good interface from a bad one and explain how to improve it. - A public track record we can read, such as GitHub, a technical blog, or a demo we can try.

Location: San Francisco, CA; New York, NY Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. ABOUT THE TECH, MEDIA & TELECOM TEAM - We work with some of the world's most influential and recognizable companies, from global telecommunications providers and leading media brands to technology platforms that power businesses worldwide. - We build agents for the moments that matter, helping our customers rise to the occasion when service disruptions, major product launches, or global events like the World Cup https://www.linkedin.com/posts/claybavor_at-sierra-we-are-very-proud-to-have-partnered-activity-7491200203899760641-I27d?utm_source=share&utm_medium=member_desktop&rcm=ACoAABYjELMBZfjrg-wrv53M1tVXGe93FF3eTww drive millions of customer interactions. - We bring Sierra’s Horizon https://sierra.ai/product/horizon vision to TMT by building agents that transform the entire customer relationship: - Telecommunications: Turn one of the most frustrating customer experiences into one of the most personal, with agents that understand each subscriber, optimize their plan and savings, anticipate opportunities to add value, and earn their loyalty over time. - Media: Turn every subscription into an ongoing, personalized relationship, with agents that help each subscriber get the most from their experience through the right content, offer, plan, and support from their free trial through retention. - Technology: Bring the white-glove customer experience traditionally reserved for the largest enterprise accounts to every customer, helping them adopt the product, discover new ways to get value, expand their usage, and successfully renew. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Create agents that pursue goals over weeks and months, reasoning about when to reach out, which channel to use, and what next action will move a customer relationship forward. - Develop personalization and experimentation systems powered by Sierra's Context Engine https://sierra.ai/blog/context-engine that combine customer data, behavior, prior conversations, and real-time context to determine the right offer or experience, then learn from every interaction and experiment to autonomously improve personalization over time. - Design conversational discovery agents that reason across huge content catalogs and rich subscriber context, using interests, history, entitlements, and the moment at hand to help someone quickly find something they'll actually want to watch, read, or listen to. - Build agents that troubleshoot deeply integrated telecommunications and connected-device experiences, reasoning across account, billing, network, and device systems to diagnose issues and take the actions needed to resolve them. - Experiment with new voice experiences and Voice Personas https://sierra.ai/blog/introducing-voice-personas tailored to each brand, customer, and moment, bringing the right empathy, energy, and conversational style to everything from navigating a frustrating telecom billing issue to helping someone discover their next favorite show or find the plan that's right for them. WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Excitement in the Tech, Media & Telecom space and a care for helping some of the world’s top brands continue to build brand loyalty with their customers. EVEN BETTER... - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.

Location: San Francisco, CA; New York, NY; Atlanta, GA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Sierra was co-founded by Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/ who first met while working together at Google over 20 years ago. Bret currently serves as Chairman of the Board of Open AI. Previously, he was co-CEO of Salesforce and CTO of Facebook. Clay spent 18 years at Google, where he most recently led Google Labs. ABOUT THE TRAVEL, TRANSPORTATION AND HOSPITALITY TEAM - The Travel, Transportation and Hospitality (TTH) supports some of the largest airlines, hotel chains, rental car brands, cruise lines and travel tech companies in the world. Our customers are frontiers in the travel space, and are true thought partners in shaping our platform, helping reinvent what hospitality looks like in this new era. Our customers rely on us to not only deliver standout customer experiences, driving stronger growth in their business. - Our TTH team is constantly pushing the bounds of what is possible within this industry and beyond. We help support our customers in the moments that matter — whether that’s proactively encouraging new bookings to prepare for exciting events, or helping guests rebook their flights or stays during times of distress. We help our customers maximize the lifetime value of their guests and build products to delight guests at every touchpoint. - We’re a small and scrappy team, and we support each other with any deliverables we have to meet. Every engineer on TTH is also a product-led thinker; every PM on TTH is tinkering and developing tangible prototypes; and every strategist on TTH is capable of owning an agent end to end. As a part of this team, you’ll set the standard on what it means to go beyond your role, and help build the travel industry of the future. WHAT YOU’LL DO - Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce. - Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way. - Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency. - Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product. EXAMPLE PROJECTS These are some examples of projects that engineers on our team have worked on recently: - Building innovative multimodal experiences: Spearhead cross-cutting initiatives, partnering with the voice and Experience SDK teams to bring to life embedded voice mode in mobile apps. This brand new product allows users to talk, tap and text with our agents all in a single view — unlocking communication through rich visualizations, and accuracy in input collection with chat, with the ease and efficiency of voice. - Shipping complex booking experiences: Build personalized booking flows, including leveraging Google Maps APIs to support searching for properties via an embedded map view, developing a recommendation engine based on past reservations and orchestrating seamless payment collection to complete the full booking lifecycle. - Abstracting complex systems into packages: Modernize legacy reservations systems by creating Sierra packages that optimize querying and updating trips for customers across the board. You’ll be challenged to think deeply about how to orchestrate each step of these workflows to maximize efficiency while upholding reliability and accuracy. - Improving the capabilities of our built in integrations: Expand platform extensibility by introducing new capabilities to our existing integrations. An example is extending our MCP integrations to support MCP UI, which allows customers to dynamically host their custom UI resources on our embedded chat windows. WHAT YOU'LL BRING - Experience building and scaling end-to-end production systems. - Strong technical problem-solving skills, especially in fast-changing, ambiguous environments. - A builder and tinkerer's mindset with high agency - you find creative ways to overcome obstacles and ship. - Comfort working directly with customers to understand their needs and solve real-world problems. - Excellent communication skills—clear, direct, and persuasive across technical and non-technical audiences. - Excitement in the travel space and a genuine care for helping improve the guest experience as a whole. Our customers care deeply about their guests, and we carry that through what we build every day. EVEN BETTER... - Language Fluency: Professional fluency in both Spanish and English. - Experience building or deploying AI/LLM systems in production - Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed - Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering - Prior experience with React, TypeScript, and/or Go - Previous roles where you interfaced with customers or led technical projects with external stakeholders OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits - Lunch, as well as delicious snacks and coffee to keep you energized when working onsite - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region and employment type, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply through the link on this page even if your experience doesn't precisely match the job description. Sierra is a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state or local laws, including veteran status and disability status. Hiring decisions are made by people, based on merit. If you need a reasonable accommodation for a disability, a religious practice, pregnancy or any related condition at any point in the application or interview process, contact us at accommodations@sierra.ai. Requests are handled confidentially and do not affect your candidacy. We will consider qualified applicants with arrest and conviction records in accordance with applicable fair chance laws.