Вакансии

AI-native приложения, агентные возможности, RAG, интеграции LLM и корпоративных систем. Python, backend/full-stack.

Location: New York, NY Workplace: Hybrid ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE You will be LangChain's dedicated cloud alliance lead for AWS, owning the relationships and revenue motions that make these partnerships produce real pipeline. This is a senior individual contributor role sitting within the Partnerships team where you'll be close to the product, close to the field, and expected to drive results without a lot of hand-holding. You'll own co-sell execution and marketplace presence end-to-end, working with cloud partner teams, field sellers, and LangChain's GTM organization to turn partner relationships into closed deals. WHAT YOU'LL DO Co-sell and pipeline - Own and grow LangChain's co-sell motion with AWS: manage joint pipeline, coordinate deals with AWS field teams, and drive sourced and influenced revenue. - Partner with LangChain sales leadership to define priority co-sell accounts, map territories to AWS coverage, and run co-sell plays region by region. - Keep ACE hygiene high across the sales team so that opportunity sharing, acceptance, and launch become routine rather than a partnerships-team chore. Marketplace - Own LangChain's AWS Marketplace presence end to end: listings, private offers, CPPO through channel partners, and program enrollment. - Operate our marketplace GTM platform (Suger today) and extend referral and offer automation so sellers can transact through Marketplace without partnerships-team involvement. Programs and funding - Operationalize AWS funding mechanisms across the team: MDF (market development funds for co-marketing), proof-of-concept credits, ISV Accelerate benefits, and any strategic collaboration funding we secure. - Pursue AWS competency and specialization programs that strengthen our positioning with AWS sellers. - Track funding drawn down against funding available and report it monthly. Executive and partner relationships - Own LangChain's working relationships at AWS: partner development managers, ISV sales managers, Marketplace category leads, and the Bedrock and AgentCore partner teams. - Build executive sponsorship on both sides, and run a joint business plan with AWS that sets shared goals and a review cadence. - Navigate the coopetitive dynamic: partner closely with AWS on Bedrock and AgentCore while differentiating LangGraph and LangSmith where AWS has competing offerings. Field enablement and marketing - Equip LangChain sales, solutions engineering, and marketing with better-together messaging, competitive positioning, and joint sales plays for AWS accounts. - Partner with marketing on co-branded campaigns, content, and events that generate pipeline, including re:Invent, AWS Summits, and joint customer programs. - Communicate results clearly to internal stakeholders, including a monthly readout on pipeline, Marketplace, and program activity. WHAT YOU'LL BRING - 6+ years in cloud alliances, partner sales, or business development, with direct, hands-on ownership of an AWS relationship. - A track record of scaling a hyperscaler co-sell motion, not just starting one: you have taken a working AWS alliance to materially higher Marketplace share, pipeline, or partner-sourced revenue, and you can describe the mechanisms that got you there. - Deep working knowledge of AWS Marketplace transactions and programs: private offers, CPPO, ACE, ISV Accelerate, and the funding programs available to ISVs. - Experience operating a marketplace GTM platform such as Suger, Tackle, or WorkSpan, including referral and offer automation. - Experience shaping and running a joint business plan with a hyperscaler, including executive sponsorship on both sides. - Enough technical foundation to speak credibly with builders. You do not need to write code, but you need to understand how LangGraph, LangSmith, and LangChain fit into a customer's AWS stack. - Experience in a startup or high-growth environment where you set the operating rhythm for a partner motion rather than inheriting one. - Strong operational discipline: you manage pipeline in the CRM, track partner activity, and report results clearly to internal stakeholders. - Excellent communication and relationship-building skills, with comfort owning senior relationships at a large cloud organization and resolving conflict constructively across company lines. NICE TO HAVE'S - Prior experience inside AWS in partner sales, ISV, or Marketplace roles, with a working understanding of how co-sell decisions and seller compensation work internally. - Experience with commercial contracts with AWS like SCAs. - Existing relationships across the AWS ISV, field, Marketplace, and Bedrock partner teams. - Familiarity with the AI/ML ecosystem: how LLMs, agents, and developer tooling fit into enterprise stacks. - Experience with AWS partner programs specific to AI and data, such as the Generative AI Competency and related partner tracks. - Prior experience at a developer tools or infrastructure company with a product-led growth motion. Annual salary range: $200,000 - $250,000 OTE + Equity COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Chicago, IL Workplace: Hybrid ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE You will be LangChain's dedicated cloud alliance lead for AWS, owning the relationships and revenue motions that make these partnerships produce real pipeline. This is a senior individual contributor role sitting within the Partnerships team where you'll be close to the product, close to the field, and expected to drive results without a lot of hand-holding. You'll own co-sell execution and marketplace presence end-to-end, working with cloud partner teams, field sellers, and LangChain's GTM organization to turn partner relationships into closed deals. WHAT YOU'LL DO Co-sell and pipeline - Own and grow LangChain's co-sell motion with AWS: manage joint pipeline, coordinate deals with AWS field teams, and drive sourced and influenced revenue. - Partner with LangChain sales leadership to define priority co-sell accounts, map territories to AWS coverage, and run co-sell plays region by region. - Keep ACE hygiene high across the sales team so that opportunity sharing, acceptance, and launch become routine rather than a partnerships-team chore. Marketplace - Own LangChain's AWS Marketplace presence end to end: listings, private offers, CPPO through channel partners, and program enrollment. - Operate our marketplace GTM platform (Suger today) and extend referral and offer automation so sellers can transact through Marketplace without partnerships-team involvement. Programs and funding - Operationalize AWS funding mechanisms across the team: MDF (market development funds for co-marketing), proof-of-concept credits, ISV Accelerate benefits, and any strategic collaboration funding we secure. - Pursue AWS competency and specialization programs that strengthen our positioning with AWS sellers. - Track funding drawn down against funding available and report it monthly. Executive and partner relationships - Own LangChain's working relationships at AWS: partner development managers, ISV sales managers, Marketplace category leads, and the Bedrock and AgentCore partner teams. - Build executive sponsorship on both sides, and run a joint business plan with AWS that sets shared goals and a review cadence. - Navigate the coopetitive dynamic: partner closely with AWS on Bedrock and AgentCore while differentiating LangGraph and LangSmith where AWS has competing offerings. Field enablement and marketing - Equip LangChain sales, solutions engineering, and marketing with better-together messaging, competitive positioning, and joint sales plays for AWS accounts. - Partner with marketing on co-branded campaigns, content, and events that generate pipeline, including re:Invent, AWS Summits, and joint customer programs. - Communicate results clearly to internal stakeholders, including a monthly readout on pipeline, Marketplace, and program activity. WHAT YOU'LL BRING - 6+ years in cloud alliances, partner sales, or business development, with direct, hands-on ownership of an AWS relationship. - A track record of scaling a hyperscaler co-sell motion, not just starting one: you have taken a working AWS alliance to materially higher Marketplace share, pipeline, or partner-sourced revenue, and you can describe the mechanisms that got you there. - Deep working knowledge of AWS Marketplace transactions and programs: private offers, CPPO, ACE, ISV Accelerate, and the funding programs available to ISVs. - Experience operating a marketplace GTM platform such as Suger, Tackle, or WorkSpan, including referral and offer automation. - Experience shaping and running a joint business plan with a hyperscaler, including executive sponsorship on both sides. - Enough technical foundation to speak credibly with builders. You do not need to write code, but you need to understand how LangGraph, LangSmith, and LangChain fit into a customer's AWS stack. - Experience in a startup or high-growth environment where you set the operating rhythm for a partner motion rather than inheriting one. - Strong operational discipline: you manage pipeline in the CRM, track partner activity, and report results clearly to internal stakeholders. - Excellent communication and relationship-building skills, with comfort owning senior relationships at a large cloud organization and resolving conflict constructively across company lines. NICE TO HAVE'S - Prior experience inside AWS in partner sales, ISV, or Marketplace roles, with a working understanding of how co-sell decisions and seller compensation work internally. - Experience with commercial contracts with AWS like SCAs. - Existing relationships across the AWS ISV, field, Marketplace, and Bedrock partner teams. - Familiarity with the AI/ML ecosystem: how LLMs, agents, and developer tooling fit into enterprise stacks. - Experience with AWS partner programs specific to AI and data, such as the Generative AI Competency and related partner tracks. - Prior experience at a developer tools or infrastructure company with a product-led growth motion. Annual salary range: $200,000 - $250,000 OTE + Equity COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Canada What the Role Is We’re hiring a Staff Software Engineer who’ll be the technical lead for a new Search team at Babylist. This new team will be focused on moving Babylist’s search capability in-house, making our search results more relevant and personalized, and partnering with other teams to transform search in the product from functional to delightful. Registry building is the heart of the Babylist product. Every parent builds a list of dozens of products, from swaddle to stroller, with real stakes (a friend or family member is going to buy these things, and a baby is going to use them). As a universal registry, this registry also typically spans many retailers. This makes registry building on Babylist one of the most interesting search and personalization problems in consumer e-commerce. This is zero-to-one work, with big ambitions. You’d build a search capability from the ground up, with a clear mandate from leadership to do it. In your first year, we expect to have rebuilt search to be highly relevant and personalized, and delivered big bets like universal search: one experience across items we sell and items from other retailers, and across products, guides and registries. We also want to work with Addie, our AI registry assistant, to have LLMs play a role in the search experience. If you want to tune an established search system, this isn’t the right role. If you’ve worked inside a strong search team and want to build a new system from scratch at a company earlier in that journey, read on. What You'll Own A Staff Engineer at Babylist sets direction. You’ll be the technical lead for search: you decide where it goes over the next year or two, sequence the bets that get there, and make the technical and product calls along the way. You’re still in the code and will drive initiatives forward across multiple teams. You’ll have software engineering and machine learning engineering support on the team. A few examples of initiatives you’d drive on the Search team: Build search in-house. Choose the architecture for indexing, retrieval and serving, and plan a seamless migration. The system you design replaces what we use today and is the foundation for everything below. Define what a good result is. Decide how we measure result quality, then improve it through query understanding, ranking and the behavioral signals we collect. Unify search across everything we show. One experience across items we sell and items from other retailers, and across products, guides and registries, including how to rank items we don’t sell next to ones we do. Decide how search and recommendations fit together. Bring what we know about a user and their registry into results, and decide how much retrieval and ranking search shares with our recommendation models. Make search conversational. Work with the Addie team, our AI registry assistant, on queries like “best stroller for urban family,” where the shopper describes a need instead of naming a product. Like every Staff Engineer here, you will: Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers. Build the platform or tooling other teams adopt by choice, and own it as it scales. Set the standard for how search builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships. Partner with product, design and data as a peer, shaping what's worth building from the start. Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones Who You Are You meet the Staff bar at Babylist. You’ve shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You’ve already changed how a team builds with AI, and the new way stuck. On top of that, you’ve worked on search problems before, ideally in an e-commerce setting. This role needs depth in the systems behind search and a clear focus on the people using it. You bring: Hands-on search experience: building and running search in production, including indexing, retrieval, ranking and query understanding. You know how to keep a search service fast, relevant and reliable as traffic and catalog size grow. Experience evaluating search quality: offline and online, including relevance judgments and A/B tests. A focus on the user: you use query data, behavior and judgment about result quality to decide what to build, and you can connect a search change to what shoppers do, and to conversion or revenue. Comfort building from zero: you can define the problem, design the system and own it end to end. You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on. Compensation We post real numbers. For a Canada-based Staff Engineer, the starting base salary range is $299,300 to $372,600 CAD, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $359,160 to $447,120 CAD. On top of that you get meaningful equity and an RRSP match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope. How We Build AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers. The Stack Core app: Rails, Packwerk, React, TypeScript, Sidekiq Mobile: iOS (Swift), Android (Kotlin) Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly Key integrations: Shopify (payments), Iterable (CRM) Why Babylist An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done. Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide. How We Work Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis. How We Hire Three rounds, usually two to three weeks start to finish. Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote. Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles. Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours. Benefits Company-paid medical and fully covered dental and vision A 401(k) match Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program Winter Wonder Week, a paid company-wide week off at the end of the year A remote-work stipend Mental-health and wellness support A Few Things to Know We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws. We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking. If you have a family member or close relationship with a Babylist employee, let your recruiter know. Official outreach only ever comes from an @babylist.com address

Location: Москва Workplace: Комбинированный VK Tech — разработчик корпоративного ПО для решения ежедневных задач бизнеса. Портфель VK Tech — это готовая экосистема программных продуктов. Ищем аналитика, который будет проектировать и настраивать поведение LLM-агентов, описывать требования, промпты, инструменты и интеграции, а также отвечать за тестирование, метрики качества и документацию жизненного цикла решения. Задачи Выявлять бизнес-задачи, которые стоит решать через AI-агентов Формулировать требования к поведению агента, его шагам, инструментам, памяти и сценариям использования Настраивать и оптимизировать промпты, RAG-пайплайны, agentic workflows и инструменты агента Тестировать ИИ-ассистентов, валидировать их ответы, анализировать логи, метрики и качество данных Документировать архитектуру, бизнес-процессы и пользовательские сценарии Проходить проектные приёмо-сдаточные испытания, описывать их программу и методику Составлять ТЗ на создание агентов и согласовывать его с заказчиками Взаимодействовать с продуктовой командой, разрабатывающей ИИ-платформу, разбираться в новом функционале продукта и использовать его в работе Требования Понимание устройства RAG, умение создавать и настраивать чанки Написание скиллов и системных промптов для агентов Знание устройства ИИ-агентов и их настройки Умение проектировать интеграции и API, понимание устройства микросервисной архитектуры Написание ТЗ, ПМИ и пользовательской документации Работа с заказчиками: выявление и описание требований, реализация ИИ-агентов по ним Навыки работы с Jira, Confluence, Python, SQL, FastAPI, LangChain, LangGraph, Haystack, Docker, Kubernetes, Postgres и векторными базами

Location: Remote: United States About Neo4j: Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community. Intelligence that works. Results that matter. Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business. Our Vision: At Neo4j, we have always strived to help the world make sense of data. As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive. Job Title: AI Solutions Architect Job Summary: As aAI Solutions Architect, you will lead the design, construction, and deployment of AI solutions that combine the power of graph databases and AI. You will act as a trusted advisor to our strategic customers, guiding them through complex data challenges and delivering transformative business value. You will have a great understanding of graph technologies, LLMs, and AI frameworks, and will be able to translate customer needs into production-ready AI applications grounded in real-world context using Neo4j Knowledge Graphs. Key Responsibilities: Solution Architecting: You will engage with technical leaders, stakeholders, and strategic partners to shape and guide the successful implementation of Graph+GenAI solutions, serving as a trusted advisor and thought partner to decision-makers throughout complex, high-impact engagements. You will design and advocate for robust, scalable solution architectures, leading the deployment of Graph+GenAI systems aligned with complex enterprise requirements and industry best practices driving architectural excellence and long-term value. You will collaborate closely with customer leadership to deeply understand their strategic objectives, translating them into high-impact AI solutions that harness the synergy of graph databases and LLMs. This includes leading the discovery of requirements, assessing enterprise data ecosystems, and identifying innovative opportunities to apply graph-based AI at scale. You will lead stakeholder engagement across all levels to steer project scope, align on priorities, mitigate risks, and ensure timely delivery—ensuring alignment between technical execution and business outcomes while maintaining a focus on measurable impact Solution Engineering: You will develop, test, and deploy production-ready AI applications that integrate graph databases with LLMs and orchestration frameworks. This involves writing production-level code, optimizing for performance and scalability, and ensuring seamless integration with customer systems. Continuously evaluate and improve the performance, scalability, and efficiency of deployed AI applications, incorporating new techniques and technologies as they emerge. Education & Enablement: You will work with other teams at Neo4j (Product and Marketing) to influence the roadmap and provide insights from the field, and package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets. You will share your expertise internally with other Neo4j teams and also with customers through workshops, training sessions, and documentation to empower them to effectively utilize, maintain, and reproduce the AI solutions you deliver. Maintain continuous learning and stay up-to-date with the rapidly evolving GenAI landscape, proactively seeking knowledge of new trends and technologies. Required Qualifications: Enterprise Application Architecture: 5+ years of experience architecting and delivering enterprise-grade applications, with a deep understanding of the full software development lifecycle and the ability to guide teams through complex design and implementation decisions. LLM Proficiency: Experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, and integrating LLMs into applications. Maintain up-to-date knowledge of different LLM providers and their strengths and limitations, as well as open-source ones). Programming Proficiency: Advanced proficiency in at least one major programming language (e.g., Java, JavaScript, Python, or C#), with a proven track record of delivering clean, maintainable, and scalable code within complex systems. Deployment and Version Control: Deep hands-on experience with deployment tooling across Linux, Docker, and Kubernetes environments, along with expert-level use of version control systems (e.g., Git, SVN) in enterprise development workflows. Cloud Computing Expertise: Demonstrated expertise in deploying and scaling applications across cloud platforms (AWS, Azure, GCP), with a strategic understanding of cloud-native architecture and DevOps best practices. Generative AI Ecosystem Knowledge: In-depth knowledge of the generative AI ecosystem, including frameworks (e.g., LangChain, LlamaIndex, Haystack) and familiarity with cloud-native AI platforms (e.g., AWS Bedrock, Google Vertex AI, Azure ML), enabling you to architect end-to-end AI solutions. Data & Analytics Fluency: Strong background in data engineering, analytics, or data science, with the ability to design data pipelines and workflows across structured and unstructured data. Hands-on experience with big data technologies (e.g., Hadoop, Spark, Hive) and database systems (SQL and NoSQL) Graph Database Authority: Deep expertise in graph data modeling and query languages (e.g., Cypher), along with practical experience working with graph databases (e.g., Neo4j, Amazon Neptune, TigerGraph) or triple stores (e.g., Ontotext, Stardog), enabling advanced knowledge graph applications Communication and Collaboration Skills: Exceptional communication and stakeholder engagement skills, with a demonstrated ability to influence cross-functional teams and align technical decisions with business goals. Problem-Solving and Analytical Abilities: Strong analytical mindset with the ability to break down complex problems, architect AI solutions, and mentor teams through implementation Willingness and ability to travel up to 50% to engage with customers, lead strategic discussions and ensure successful project execution. The annual on target earnings range for this position based in the United States is listed below. This range is an estimate, and the actual on target earnings may vary based on Neo4j’s compensation practices, job related skills, depth of experience, relevant certifications and trainings, in addition to geographic location. Based on the factors above, Neo4j utilizes the full width of the range. In addition to the range below, US employees are eligible for a stock option grant and certain roles are eligible for an annual bonus. Employees in this position are also eligible to participate in the Company’s standard benefit programs, which currently include the following: medical, dental, and vision benefits, 401(k), paid time off, and certain leaves of absence. Annual On Target Earnings Range $160,000 — $220,000 USD Why Join Neo4j? Neo4j is, without question, the most popular graph intelligence platform in the world. We have customers in every industry globally, and our products are a proven product/market fit. Joining our team is an opportunity to shape the future of data and analytics. Below are just a few exciting facts about Neo4j. Neo4j is one of the fastest-scaling technology companies in this industry. It recently surpassed $200M in annual recurring revenue (ARR), doubling its ARR over the past three years. Raised the biggest funding round in database history ($325M Series F). Backed by world-class investors like Eurazeo, GV (formerly Google Ventures), and Inovia Capital, Neo4j has raised over $600M in funding and is currently valued at over $2Bn. This puts Neo4j among the most well-funded database companies in history. 84% of the Fortune 100 and 58% of the Fortune 500 use Neo4j. Examples include Boston Scientific , BT Group , Caterpillar , Cisco , Comcast , Department for Education UK , eBay , NBC News , Novo Nordisk , Worldline , and others . Co-founder and CEO Emil Eifrem has built an amazing culture that prides itself on relationships, inclusiveness, innovation, and customer success. Countless industry awards . Massive enterprises and individual developers/data scientists love Neo4j. A strong sense of community and ecosystem is built around the platform. A recent Forrester Total Economic Impact™ Study cited Neo4j as delivering 417% ROI to customers. Research shows that members of underrepresented communities are less likely to apply for jobs when they don’t meet all the qualifications. If this is part of the reason you hesitate to apply, we’d encourage you to reconsider and give us the opportunity to review your application. At Neo4j, we are committed to building awareness and helping to improve these issues. One of our central objectives is to provide an inclusive, diverse, and equitable workplace for everyone to develop their potential and have a positive, career-defining experience. We look forward to receiving your application. Neo4j Values: Neo4j is a Silicon Valley company with a Swedish soul. We foster collaboration and each of us is empowered to contribute and put our innovative stamp on projects. We hire candidates who reflect the following Neo4j core values: (we)-[:VALUE]->(relationships) (we)-[:FOCUS_ON]->(userSuccess) (we)-[:THRIVE_IN]->(:Culture {type: [‘Open’, ‘Inclusive’]}) (we)-[:ASSUME]->(:Intent {direction:’Positive’}) (we)-[:WELCOME]->(:Discussions {nature: ‘IntellectuallyHonest’}) (we)-[:DELIVER_ON]->(ourCommitments) Neo4j is committed to protecting and respecting your privacy. Please read the privacy notice regarding Neo4j's recruitment process to understand how we will handle the personal data that you provide. More information at www.neo4j.com . ©2026 Neo4j, Inc., Neo Technology®, Neo4j®, Cypher®, Neo4j Bloom™, Neo4j Graph Data Science Library™, Neo4j® Aura™, and Neo4j® AuraDB™ are registered trademarks or a trademark of Neo4j, Inc. All other marks are owned by their respective companies.

-Развивать HTTP API и бизнес-логику двух асинхронных Python-сервисов на FastAPI. -Проектировать и реализовывать RAG-пайплайны: retrieval, query rewriting, multi-hop поиск, сбор контекста, structured output, цитирование источников и обработку частичных ответов.

Location: Remote - Australia; Remote - Singapore Workplace: Remote ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE We're hiring a Regional Vice President to own and lead our APAC business. You'll inherit a team of four quota-carrying enterprise AEs across Australia, Singapore and be responsible for building the management layer, operating model, and partner ecosystem that takes APAC from early traction to consistent, scaled revenue. This is a Director-level hire with second-line ambition. You'll report directly to the Global Vice President of Sales and operate with meaningful autonomy across pipeline, hiring, partner relationships, and executive engagement.   WHAT YOU'LL OWN Team leadership and performance - Lead, develop and expand the Enterprise Sales teams across the APAC region - Run weekly pipeline reviews, deal coaching sessions, and forecast calls with precision and consistency - Identify and close performance gaps early: coach the team to close larger deals faster and navigate complex, multi-stakeholder cycles - Build a culture of accountability and development; create clear career paths for senior individual contributors, including first-line management opportunities as the team scales Revenue - Own the APAC number: quarterly and annual quota attainment across all three sub-regions - Build and maintain a healthy pipeline that supports consistent delivery and predictable forecasting to Global VP of Sales and leadership - Engage directly in strategic deals as executive sponsor, bringing credibility and commercial weight to enterprise negotiations - Establish the region's strongest lighthouse accounts across key industry verticals, building referenceable wins that anchor LangChain's market position in APAC Hiring - Manage multiple open roles across APAC simultaneously: owning the full hiring lifecycle across pipeline, assessment, and closing - Partner with the internal talent team to move at pace without compromising on quality - Define the headcount profile for APAC beyond Q4 and feed into H1 planning, ensuring the team is built ahead of the revenue curve Partner ecosystem - Owns hyperscaler and GSI/RSI relationships (AWS, Google Cloud, Azure, and key SIs) across APAC - Develop a structured partner motion that generates qualified pipeline and supports deal acceleration, reduces risk and drives expansion - Represent LangChain at partner QBRs and executive engagements in region Market presence - Represent LangChain as a keynote-ready leader at partner events, customer engagements, and industry conferences across the region - Build LangChain's brand with technical buyers, CIOs, and innovation leaders across APAC's most important enterprise accounts - Bring intelligence on the APAC markets back to the Global VP of Sales and product teams to inform roadmap and go-to-market positioning   WHAT WE'RE LOOKING FOR Experience - 8+ years in enterprise SaaS sales, with at least 3 years in a regional or sub-regional leadership role managing quota-carrying AEs - Demonstrable track record of hitting and exceeding regional revenue targets across multiple quarters - Experience managing teams across multiple countries and time zones, with the cultural intelligence to operate across the APAC region - Background selling to technical buyers (engineering leaders, CTOs, platform teams): you understand how developer tools get evaluated and adopted - Experience in the AI, data, or developer tooling space strongly preferred; familiarity with the LangChain ecosystem is a meaningful plus Leadership - You've run teams of 6+ AEs before and know the difference between managing and coaching - You can hold a forecast conversation with a VP and a deal coaching session with an AE in the same afternoon, and add value in both - You hire well and fast. You know what good looks like for enterprise AE profiles and you can run structured hiring processes across four open roles simultaneously - You've built or contributed to a partner motion before: you understand what "partner pipeline" means in practice, not just in theory Operating style - You bias toward action. You don't wait for a playbook to be handed to you: you build it - You're comfortable with ambiguity and early-stage scale. This is not a role with a fully defined motion; you'll shape a significant part of it - You communicate clearly and directly, to your team and to leadership - You're present in the market. You attend the right events, know the right people, and build relationships that translate into pipeline and retention   COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: London Workplace: OnSite ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE We are looking for a Director, EMEA Professional Services to build and lead our services and customer engineering motion across Europe, the Middle East, and Africa. This is a player-coach leadership role at the center of the EMEA go-to-market. You will shape how we engage EMEA customers after the sale and alongside it. You will help Sales position and sell both the subscription and, when it fits, services. You will own staffing and delivery for EMEA engagements. You will also coordinate the wider Customer Engineering team in region, including Enablement Engineers, Activation Specialists, and Account Managers. You will work closely with EMEA GTM leadership and stay aligned with global Professional Services leadership. EMEA should feel like one team with the rest of PS, with the local context it needs to win. Location: London preferred. Open to other EMEA locations with strong overlap with UK and European business hours. Some travel to customers and to our San Francisco and New York offices is expected. WHAT YOU'LL DO - Define EMEA Customer Engineering programs: Partner with EMEA GTM leadership to design and run programs for the region. This includes onboarding, activation, enablement, and services offerings. Adapt global programs to regional needs such as data residency, regulated industries, language, and partner ecosystems. - Support positioning and selling: Support the creation and evolution of standard pre sales assets to support the AEs with positioning Professional Services. Work with Account Executives and Solutions Engineers on deal strategy. Help position the subscription and the right post-sale path for each customer. Join executive conversations when needed. Scope and sell Professional Services when it is the right fit. Review SOWs, estimates, and pricing for EMEA deals. - Own resource management and delivery: Own staffing, capacity planning, and utilization for the EMEA PS team. Match engagements to the right people and practices. Make sure delivery follows PS methodology, including scoping, technical review, documentation, and customer handoff. Review key deliverables, surface risk early, and handle escalations. - Lead and grow the EMEA team: Hire, onboard, coach, and develop Architects, AI Engineers, and Engagement Managers in region. Set clear expectations and give direct feedback. Build a team culture with a high bar for quality and craft. - Coordinate across global Customer Engineering in a matrix model: Provide day-to-day coordination and supervision for EMEA Enablement Engineers, Activation Specialists, and Account Managers. Set shared priorities and make sure customers get a connected journey from activation to enablement to services to expansion. Work with their functional leaders on performance, growth, and standards. - Align with global PS leadership: Keep delivery standards, tooling, pricing, and reporting consistent across regions. Share what works in EMEA. Bring back playbooks, reusable assets, and process improvements from the global team. Contribute to the PS operating rhythm and roadmap. - Run the business: Own EMEA PS bookings, utilization, delivery margin, and customer outcomes. Report on pipeline, capacity, and risk to Customer Engineering and GTM leadership. - Stay close to customers: Remain active in key accounts. Act as the senior escalation point for strategic EMEA customers. Be a credible voice with technical and executive stakeholders. WHAT YOU'LL BRING - You have 10+ years of experience in professional services, solutions engineering, customer engineering, or consulting. At least 4 of those years were in leadership roles. - You have led a services or post-sales team in EMEA. You know the regional market and its regulatory landscape. - You have helped sell technical services alongside a software subscription. You can scope work, price it, and defend it with customers. - You have owned resource management and delivery. You understand utilization, capacity planning, and delivery quality. - You have led through influence in a matrix organization. You can set direction for people who do not report to you. - You are credible with engineers and executives. You can discuss agent architectures, cloud infrastructure, and enterprise AI adoption. - You have built programs from scratch in a fast-moving environment. You do not wait to be told what to do. - You communicate clearly and directly. You work well across time zones with a global team. You exemplify our operating principles - You are motivated to build something great. You hold a high bar for quality, craft, and impact. - You embrace hot takes. You share informed opinions, challenge the status quo, and engage in constructive debate. - You operate with maximum agency. You take ownership, move work forward independently, and help others unblock. - You run to the roar. You lean into hard problems, ambiguity, and fast-moving challenges. NICE TO HAVE - Hands-on experience with AI/ML, LLM applications, or agent frameworks - Experience with SaaS subscriptions, usage-based pricing, and services attach - Experience working with SIs and cloud marketplaces in EMEA - Experience in a high-growth startup or open-source company - Fluency in one or more European languages in addition to English HOW SUCCESS WILL BE MEASURED - EMEA customers have clear programs and a connected post-sale journey. - Services attach rate and bookings grow in the region, with healthy margins. - EMEA PS meets its utilization target over time, with exceptions understood and managed. - Delivery consistently follows PS standards, and material risks surface early. - Matrix partners in Enablement, Activation, and Account Management are aligned on EMEA priorities. - EMEA practices stay consistent with global PS and feed improvements back to it. COMPENSATION AND BENEFITS We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: Hybrid ABOUT US At LangChain, our mission is to enable every company to own its intelligence. We believe agents will transform how companies operate, and we're building the foundation to make that future possible. Our open-source harnesses and LangSmith platform give developers and enterprises the infrastructure to run, improve, and govern agents at scale. We've raised $460M to date, with our most recent funding round valuing the company at $3B, backed by leading investors including Sequoia, Benchmark, IVP, and CapitalG. As we continue to expand our platform and tackle some of the hardest challenges in agent engineering, every team member has the opportunity to make a meaningful impact and help shape both our technology and the future of the industry. More than 7,000 organizations rely on LangSmith, from fast-growing startups to Fortune 500 enterprises, including NVIDIA, Bridgewater, LinkedIn, Workday, and Rippling. We're just getting started on making high-performing agents easier to build and manage at scale. ABOUT THE ROLE You will be LangChain's dedicated cloud alliance lead for AWS, owning the relationships and revenue motions that make these partnerships produce real pipeline. This is a senior individual contributor role sitting within the Partnerships team where you'll be close to the product, close to the field, and expected to drive results without a lot of hand-holding. You'll own co-sell execution and marketplace presence end-to-end, working with cloud partner teams, field sellers, and LangChain's GTM organization to turn partner relationships into closed deals. WHAT YOU'LL DO Co-sell and pipeline - Own and grow LangChain's co-sell motion with AWS: manage joint pipeline, coordinate deals with AWS field teams, and drive sourced and influenced revenue. - Partner with LangChain sales leadership to define priority co-sell accounts, map territories to AWS coverage, and run co-sell plays region by region. - Keep ACE hygiene high across the sales team so that opportunity sharing, acceptance, and launch become routine rather than a partnerships-team chore. Marketplace - Own LangChain's AWS Marketplace presence end to end: listings, private offers, CPPO through channel partners, and program enrollment. - Operate our marketplace GTM platform (Suger today) and extend referral and offer automation so sellers can transact through Marketplace without partnerships-team involvement. Programs and funding - Operationalize AWS funding mechanisms across the team: MDF (market development funds for co-marketing), proof-of-concept credits, ISV Accelerate benefits, and any strategic collaboration funding we secure. - Pursue AWS competency and specialization programs that strengthen our positioning with AWS sellers. - Track funding drawn down against funding available and report it monthly. Executive and partner relationships - Own LangChain's working relationships at AWS: partner development managers, ISV sales managers, Marketplace category leads, and the Bedrock and AgentCore partner teams. - Build executive sponsorship on both sides, and run a joint business plan with AWS that sets shared goals and a review cadence. - Navigate the coopetitive dynamic: partner closely with AWS on Bedrock and AgentCore while differentiating LangGraph and LangSmith where AWS has competing offerings. Field enablement and marketing - Equip LangChain sales, solutions engineering, and marketing with better-together messaging, competitive positioning, and joint sales plays for AWS accounts. - Partner with marketing on co-branded campaigns, content, and events that generate pipeline, including re:Invent, AWS Summits, and joint customer programs. - Communicate results clearly to internal stakeholders, including a monthly readout on pipeline, Marketplace, and program activity. WHAT YOU'LL BRING - 6+ years in cloud alliances, partner sales, or business development, with direct, hands-on ownership of an AWS relationship. - A track record of scaling a hyperscaler co-sell motion, not just starting one: you have taken a working AWS alliance to materially higher Marketplace share, pipeline, or partner-sourced revenue, and you can describe the mechanisms that got you there. - Deep working knowledge of AWS Marketplace transactions and programs: private offers, CPPO, ACE, ISV Accelerate, and the funding programs available to ISVs. - Experience operating a marketplace GTM platform such as Suger, Tackle, or WorkSpan, including referral and offer automation. - Experience shaping and running a joint business plan with a hyperscaler, including executive sponsorship on both sides. - Enough technical foundation to speak credibly with builders. You do not need to write code, but you need to understand how LangGraph, LangSmith, and LangChain fit into a customer's AWS stack. - Experience in a startup or high-growth environment where you set the operating rhythm for a partner motion rather than inheriting one. - Strong operational discipline: you manage pipeline in the CRM, track partner activity, and report results clearly to internal stakeholders. - Excellent communication and relationship-building skills, with comfort owning senior relationships at a large cloud organization and resolving conflict constructively across company lines. NICE TO HAVE'S - Prior experience inside AWS in partner sales, ISV, or Marketplace roles, with a working understanding of how co-sell decisions and seller compensation work internally. - Experience with commercial contracts with AWS like SCAs. - Existing relationships across the AWS ISV, field, Marketplace, and Bedrock partner teams. - Familiarity with the AI/ML ecosystem: how LLMs, agents, and developer tooling fit into enterprise stacks. - Experience with AWS partner programs specific to AI and data, such as the Generative AI Competency and related partner tracks. - Prior experience at a developer tools or infrastructure company with a product-led growth motion. Annual salary range: $200,000 - $250,000 OTE + Equity COMPENSATION PHILOSOPHY: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Москва АС "Платформа Кибербезопасности" . В основе решения используются продукты SDP Hadoop и SDP Ozone в качестве BigData хранилищ и обработки данных. В контуре сопровождения несколько высоконагруженных кластеров и более 3000 потоков обработки данных Обязанности * настройка, поддержание работоспособности и развитие промышленных и тестовых сред (Hadoop, Ozone, Kafka, Spark, Flink) * обновление ОС на стендах (SberLinux OS Server, RHEL) и контроль версий ПО * устранение возникающих инцидентов и технологических задач по компонентам платформы * устранение рисков кибербезопасности (уязвимости компонентов, compliance-несоответствия) * участие в задачах развития платформы в части повышения надёжности и стабильности компонентов * подготовка и проведение приёмо-сдаточных испытаний, внедрение новых версий ПО * настройка и поддержка интеграционных взаимодействий со смежными системами АС Антифрод * проведение риск-менеджмента и capacity-менеджмента * управление дефектами и проблемами в Jira/ITSM * развитие процессов автоматизации DevOps, CI/CD и ротации секретов * развитие инфраструктурного и прикладного мониторинга компонентов системы. Требования *  опыт сопровождения и администрирования высоконагруженных автоматизированных систем в финтехе * знакомство со стеком: Apache Flink, Apache NiFi, Apache Spark, Kubernetes, Docker * опыт настройки Ranger / Sentry (управление доступом в Hadoop) * опыт работы с secman / HashiCorp Vault (управление секретами) * знакомство с AI/ML-инфраструктурой (LlamaIndex, LangChain, векторные БД) * опыт миграционных проектов (vendor replacement, инфраструктурная миграция) * знание ClickHouse, Nginx * опыт автоматизации DevOps и CI/CD пайплайнов. Условия * работа в офисе * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * более 400 образовательных программ СберУниверситета для профессионального и карьерного развития * программа адаптации и помощь руководителя на старте (для Junior позиций) * 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: Москва «История операций» — это один из самых высоконагруженных и посещаемых экранов в приложении. Наша цель — превратить сухие строчки чеков в умную, интерактивную ленту. Мы внедряем LLM, чтобы пользователь мог общаться со своими финансами на естественном языке, получать моментальные умные инсайты, автоматические теги и персонализированную аналитику расходов. Обязанности * Разрабатывать и внедрять ИИ-агентов (LLM Agents): проектировать логику рассуждений агентов на базе GigaChat, обучать и дообучать модели (Finetuning, LoRA/QLoRA), настраивать вызов внешних инструментов (Tool Calling, API, SQL-скрипты) под задачи банкинга. * Проектировать и обучать классические ML-модели: разработать точечную ML-модель для анализа транзакционных и табличных данных (классификация, кластеризация или скоринг) для обогащения контекста агента. * Строить RAG-системы: проектировать архитектуру контекстного поиска ответов по сложным финансовым логам, чекам и документам пользователя. * Анализировать и дорабатывать корзину запросов: оценивать результаты ответов агентов на предмет качества и ошибок, согласовывать метрики (Guardrails, Ragas), защищать подходы перед бизнесом и показывать ценность данных на понятном языке. * Обеспечивать надёжность и оптимизировать воркфлоу: минимизировать задержки (latency) ответов, настраивать мониторинг внедрённых решений и контролировать траекторию поведения агента, полностью исключая галлюцинации в продакшене. Требования Наш идеальный кандидат * Имеет опыт в LLM от 2-3 лет: запускал языковые модели в продакшн (Transformers, BERT, GPT-подобные архитектуры). * Мастерски владеет Python: знает библиотеки PyTorch, Hugging Face, LangChain, LlamaIndex. * Понимает специфику работы с LLM: умеет эффективно настраивать Prompt Engineering, оптимизировать инференс (vLLM, TensorRT-LLM) и оценивать качество генерации (Ragas, TruLens). * Обладает базой в классическом машинном обучении: понимает алгоритмы Classic ML, умеет работать с табличными данными и признаками (CatBoost / LightGBM / Scikit-learn). * Дружит с Big Data: уверенно пишет сложные запросы на SQL (Hive/Spark) для подготовки датасетов. Условия Почему это вакансия-мечта * Масштаб и влияние: ваш код и обученные модели будут работать в смартфонах каждого второго жителя страны. * Топовый стек и ресурсы: доступ к мощным суперкомпьютерам Сбера для обучения крупнейших моделей. * Минимум бюрократии: мы работаем по гибким методологиям внутри сильного DS-сообщества. * Забота и бенефиты: конкурентная белая зарплата, годовые бонусы, ДМС * Тренажерный зал (работает даже сейчас) * Современный IT-офис с пуфами, игровыми зонами и т.д. * Умопомрачительные виды на Москву Профильное обучение, митапы, конфы, воркшопы внутри и вне компании Если вы хотите быть у истоков создания принципиально новой, умной истории операций — давайте создавать будущее финтеха вместе!

Location: Москва SberTech — одна из крупнейших IT-компаний в России. Наш основной заказчик — Сбер, но мы стремимся создавать высоконадежные (99.99) продукты, востребованные на рынке в разных сферах бизнеса. Мы развиваем _Platform V Synapse_ — интеграционную платформу Сбера. Это облачное решение для интеграции и миграции сервисов, обрабатывающее миллионы запросов. Наши продукты являются базовым технологическим слоем для внедрения agentic ai в части всех взаимодействий агентов и служат enabler’ми для AI-трансформации бизнеса. Мы — команда, сочетающая опыт и глубокие знания с активной позицией. Работаем по Agile, используем собственный производственный конвейер. Автоматизированное тестирование и CI/CD — основа нашего процесса разработки. Мы способствуем развитию экосистемы Сбербанка, создавая важные интеграционные элементы. Но не ограничиваемся им – наши продукты широко известны на рынке Российского ПО. Обязанности * проектирование и развитие архитектуры GenAI-решений от прототипа до production, выбор паттернов (prompt-based, RAG, агенты, fine-tuning) * построение LLM-пайплайнов: RAG (chunking, embeddings, reranking), управление контекстом, tool use / function calling * внедрение LLMOps-практик: observability, трассировка, guardrails, тестирование качества * участие в проектировании архитектуры и разработке микросервисов и базовых компонентов платформы (backend, микросервисы, cloudnative) * руководство командой сотрудников, управлением процессом производства ПО: декомпозиция, delivery, code и architecture review, инженерные стандарты, управление качеством * работа с продуктом: анализ потребностей пользователей, полный цикл работы с продуктовыми гипотезами с ИИ-составляющей. Требования * опыт коммерческой разработки от 5 лет: backend, микросервисы, K8s, желательно Golang * опыт управления командой разработки от 2 лет * опыт в AI/ML и GenAI с кейсами вывода решений в ПРОМ * опыт применения паттернов проектирования и принципов построения высоконагруженной микросервисной архитектуры * опыт реализации AI-агентов (LangChain / LangGraph / ReAct / MCP / A2A) * применение практик работы с LLM: ограничения, галлюцинации, context window management. ### Будет плюсом опыт: * проектирования мульти-агентных систем и сложной оркестрации * работы с временными рядами, аномалиями, прогнозированием * работы с Istio Service Mesh, разработки Kubernetes-операторов и сетевых решений * внедрения AI-практик и решений в платформенные инструменты, инфраструктурные решения и PaaS-сервисы. Условия * гибридный формат работы * годовой бонус и ежегодный пересмотр зарплаты * статус аккредитованной ИТ-компании * расширенный ДМС с первого дня и льготное страхование для семьи * корпоративный университет Сбера, внутренняя образовательная платформа, участие в IT-конференциях * 90 дней удаленной работы из любого региона РФ * льготная ипотека в Сбере, подписка Прайм с возможностью совместного использования на трёх близких.

Location: Москва Мы формируем ядро команды, которая создает с нуля экосистему интеллектуальных агентов для автоматизации бизнес-процессов. Нам нужен универсальный специалист, способный вести фичи от проектирования базы данных до реализации сложного интерактивного интерфейса. Наша цель - разработка готовых решений «под ключ». Вы будете работать на стыке бэкенда, машинного обучения и фронтенда, напрямую влияя на то, как тысячи сотрудников банка взаимодействуют с новыми инструментами оптимизации. Обязанности * разработка backend для AI-агентов * интеграция с API существующих АС * реализация RAG-пайплайнов * оптимизация производительности * сode review. Требования * 3+ года в backend-разработке * python (FastAPI, Django) / Java / Go * опыт работы с LLM-фреймворками (LangChain, LlamaIndex) * postgreSQL, Redis, MongoDB * vикросервисы, event-driven архитектура. Условия * комфортный современный офис г. Москва, Кутузовская 32 * гибридный формат работы * ежегодный пересмотр зарплаты, годовая премия * корпоративный спортзал и зоны отдыха * система обучения для профессионального и карьерного развития * расширенный полис ДМС с первого дня работы и страхование для семьи * программа ипотеки для сотрудников * подписка Прайм с возможностью совместного использования на трёх близких * вознаграждение за рекомендацию друзей в команду Сбера.

Location: Romania; Serbia; Poland; Singapore; Malaysia J ob Overview We're looking for a hands-on Technical Lead who still loves writing code. You'll build features across our React/Next.js front ends and our Django, PHP and Magento back ends. You'll review your team's code and keep the work moving every day. This is a player-coach role. Expect roughly half your time on hands-on development and half on reviews, planning and leading a team of 8–12 engineers. You'll work closely with Product, QA and DevOps to turn ideas into reliable features that ship on time. What you'll do Build features (hands-on) Design, build and ship features end to end, from React/Next.js screens to Django, PHP or Magento back-end logic and APIs. Take on the hardest technical problems yourself: performance, integrations, tricky bugs. Write clean, tested, maintainable code that sets the standard for the team. Review code and raise quality Review pull requests every day, giving clear and kind feedback that helps people grow. Set and maintain coding standards, branching rules and a clear definition of done. Work with QA to keep production bugs low and fix critical issues fast. Lead the team and keep work moving Break features into clear tasks, estimate effort and plan sprints with the Product Manager. Support daily stand-ups, spot blockers early and clear them. Mentor junior and mid-level engineers through pairing, reviews and regular one-to-ones. Keep stakeholders updated on progress, risks and trade-offs in plain language. Shape the technical direction Make architecture decisions and write them down so everyone understands why. Improve CI/CD, monitoring and release processes with DevOps. Help plan upgrades, reduce technical debt and keep the platform secure. Must-have skills React and Next.js: strong, hands-on experience building production apps with hooks, TypeScript, server-side rendering and state management (Redux Toolkit, Zustand or similar). Back-end (at least one, ideally two): Django / Python: REST APIs (Django REST Framework), ORM, migrations, background jobs. PHP / Magento 2: custom modules, plugins and observers, checkout and catalogue customisation, performance tuning. APIs and databases: designing REST or GraphQL APIs, and working with MySQL or PostgreSQL, query optimisation and caching (Redis). Code quality: writing and enforcing unit and integration tests, and running thorough, constructive code reviews. Engineering practices: Git workflows, CI/CD pipelines, Docker, and cloud basics (Azure or AWS). Security: OWASP basics, safe handling of secrets and user data, and secure authentication. Leadership: at least 2 years leading or mentoring a team, planning sprints and keeping delivery on track. Communication: clear written and spoken English, and comfortable working with teams across time zones. Good to have AI technologies: hands-on work with LLM APIs (OpenAI, Anthropic, Azure OpenAI), RAG pipelines, vector databases (pgvector, Pinecone), or frameworks like LangChain or LlamaIndex. Building AI features into real products, such as chatbots, smart search, recommendations or content generation. Using AI coding tools (Claude Code, GitHub Copilot, Cursor) responsibly, with clear review practices for the team. E-commerce experience, especially Magento 2 with a headless Next.js front end. Kubernetes, Azure DevOps, or infrastructure as code (Terraform). Performance work such as Core Web Vitals, caching layers, and CDNs like Azure Front Door or Cloudflare. Experience in Agile/Scrum teams using Jira and Confluence. Experience and education 7–10 years of software development, with at least 3 years as a tech lead or senior engineer guiding others. A proven record of shipping full-stack features to production. A degree in Computer Science or a related field, or equivalent practical experience. Salary: $6,000 – $8,000 / month

Location: Ukraine; Poland; Spain; Portugal; Romania; Czechia At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. We are looking for a Middle ML & AI Engineer to join us as part of our team. About the role PitchBook’s Machine Learning Engineer is responsible for using machine learning, statistical modeling, and natural language processing (NLP) to collect a high volume of data for the PitchBook Platform and surface insights for the capital markets. This role will also serve as a resource and mentor for junior members of the team. A strong motivation to succeed is critical, and everyone has the opportunity to shape the long-term direction of our team. About the project PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. Features of PitchBook: Advanced search / Discovery & insights / Company profiles / Workflow & efficiency / Financials, and many more. Team: Engineering Manager, 6 MLE’s. Work Environment: The role offers a flexible work schedule, allowing you to adapt your working hours with the requirement to attend all team meetings. The team follows a Scrum-based Agile methodology. Technical Stack: Python, PyTorch, Scikit-Learn, Spacy, LangChain, LangGraph etc. As a qualified expert, You will Work with GenAI & LLMs: Design, develop, and fine-tune generative AI models using transformer architectures. Implement advanced techniques to create practical solutions for real-world challenges. Use Modern Toolkits: Leverage frameworks like LangChain, LangGraph, and LangSmith to build automated pipelines and intelligent agents. Integrate these tools with vector databases for efficient similarity search and real-time analysis. Extract Data Insights: Process and analyze large volumes of unstructured data using embeddings and statistical modeling to identify meaningful insights. Build Scalable Systems: Collaborate with cross-functional teams to create production-grade ML systems that handle real-time, high-volume data processing. Collaborate & Communicate: Work with Product and Engineering teams to improve data management and support innovation. Present complex analyses clearly and effectively. Tech Stack & Focus Areas: Work with generative AI and transformer models, integrating frameworks like LangChain, LangGraph, and LangSmith to automate workflows and build intelligent systems. Use PyTorch, Scikit-Learn, and Spacy to build NLP pipelines. Implement vector databases for high-dimensional data embeddings and develop hybrid models to extract insights from diverse data sources. We’re looking for you if you have Educational Background: You hold a Bachelor’s or Master’s degree in Computer Science, Machine Learning, Statistics, or a related field. Experience: You bring 4+ years of production experience in the ML field, with a track record in developing transformer-based models and deploying them in scalable systems. Technical Expertise: Proficient in Python and machine and deep learning frameworks like TensorFlow, PyTorch, ScikitLearn, Spacy, or others; experienced in natural language processing and modern LLM-based techniques; experience with full ML lifecycle, data preprocessing, training, evaluation stage, and monitoring techniques; skilled with SQL and data extraction methods. Innovative Thinker: You thrive on solving complex problems and are always exploring new trends in Generative AI. Collaborator & Communicator: You’re an excellent communicator able to collaborate and professionally express your thoughts to team members, other engineering teams, and stakeholders. Domain Knowledge: Exposure to financial services, investment banking, venture capital, or private equity is nice to have. Languages: English —Upper-Intermediate or higher; Ukrainian —fluent/native . What’s in it for You Reveal great tech solutions Join the team of experts who create custom, cutting-edge tech solutions for world-renowned businesses, fueling clients growth. Unleash your potential, tackle new challenges, and be part of a team that values your skills and contributions. Focus on long-term impact and building tailored, long-lasting partnerships with our clients. Experience an agile and flexible working environment Work fully remote around the globe, or in a hybrid work model from our office hubs which are equipped with everything needed for comfortable work. Enjoy a flexible working schedule and create work and rest balance for yourself. Empower yourself with a stable workload and a stable income, focusing on lasting cooperation and high-performance culture. Embrace the opportunity for personal and professional growth Take advantage of performance review and career path. Elevate your skills with mentorship program, personal development plan, and individual learnings through the corporate library, public speaking support, and more. Feel cared about Be among like-minded people and feel supported with collaboration, open communication and mutual respect. Join company-wide tech and cultural events, and contribute to meaningful CSR initiatives that resonate with your values. Interview steps Pre-Screening with the recruiter Technical interview (up to 90 min) System Design interview (up to 45 min) Final interview with Engineering Manager (60 min)

-Разработка и внедрение AI-агентов для автоматизации внутренних процессов (чат-боты, интеллектуальная обработка документов, автономные системы). -Проектирование, внедрение и оптимизация RAG-систем (поиск по базам знаний, корпоративным данным, векторные хранилища).

-Разрабатывать AI-агентов и мультиагентные сценарии для автоматизации различных этапов PDLC. -Развивать Ассистента платформы на базе LLM.