Задачи:
— Работа с Docker и системами оркестрации контейнеров Kubernetes
— Управление конфигурациями с помощью Ansible, ArgoCD и инструментов IaC Terraform
— Построение CI/CD пайплайнов с использованием GitLab CI и Jenkins
— Работа с системами мониторинга и логирования: Prometheus, VictoriaMetrics, Grafana, Loki, ELK
— Администрирование Linux и сетевые взаимодействия в микросервисной архитектуре
— Изучение новых технологий (мультиагентные фреймворки, RAG, MCP) и предложение улучшений
— Понимание жизненного цикла AI-агентов и ML-моделей
— Разработка и развертывание автономных AI-агентов с использованием MCP, RAG
— Работа с платформами для оркестрации агентов и serverless-средами
— Интеграция корпоративных систем (OneWork, SberSpace)
— Интерес к искусственному интеллекту и агентным системам
Условия:
— Работа в стабильной компании с официальным трудоустройством по ТК РФ с первого дня
— "Белая" заработная плата
— Расширенный социальный пакет: ДМС (включая стоматологию), корпоративные скидки на фитнес, спортивные секции
— Профессиональное обучение и развитие
— Современная техника, мощный ноутбук предоставляется в день оформления
— Формат работы: строго офис, Москва
Задачи:
— Получать задачи от внутренних заказчиков и погружаться в их бизнес-процессы.
— Выявлять, какие процессы можно и целесообразно автоматизировать с помощью AI.
— Формировать ТЗ, декомпозировать задачи и предлагать варианты реализации.
— Проектировать структуру AI-автоматизации и самостоятельно реализовывать решения.
— Работать с Claude, ChatGPT и другими LLM.
— Создавать AI-ассистентов, AI-агентов и базы знаний.
— Настраивать интеграции с CRM, 1С, сайтами, мессенджерами, телефонией и другими системами.
— Работать с API, RAG, embeddings и автоматизированными workflow.
— Тестировать, дорабатывать и повышать качество AI-решений.
— Описывать готовые решения, создавать инструкции и базу знаний.
— В перспективе выстраивать процессы разработки и управлять командой AI-разработчиков.
Требования:
— Опыт работы в AI / AI Automation / Backend / Integration от 3 лет.
— Практический опыт работы с Claude, ChatGPT и LLM.
— Опыт создания AI-решений и автоматизации бизнес-процессов.
— Понимание API, интеграций, RAG, embeddings, AI-агентов.
— Системное мышление и способность самостоятельно разобраться в новой задаче.
— Умение общаться с бизнес-заказчиками и переводить их запросы в техническое ТЗ.
— Навык самостоятельно вести задачу от постановки до готового результата.
— Ответственность за качество и результат внедрения.
Будет плюсом:
— Python, SQL/PostgreSQL, n8n, Make, Docker, MCP, опыт создания AI-агентов, CRM/1С и опыт управления разработчиками.
Условия:
— Офис в Москве, рядом с м. ЦСКА.
— График 5/2: 09:00–18:00 или 10:00–19:00.
— Заработная плата обсуждается по итогам собеседования.
— Реальные задачи по внедрению AI в бизнес, возможность видеть результат своей работы.
— Возможность влиять на технологии и формировать AI-направление внутри компании.
— Перспектива роста в Team Lead / руководителя направления.
— Профессиональная команда и возможности для развития.
— Современный офис класса А.
— Скидки на услуги компании.
Location: New York, New York, United States
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:
New York City
Experience Level:
8+ years
Compensation:
$200,000–$250,000 base salary + equity
Work Model:
In-office, typically three to five days per week, depending on client requirements
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 in-office:
Our work is client-first, which means in-person collaboration may be required either at the client site or at our planned Manhattan office near Madison Square Park. Depending on your assignment and client needs, you should expect to work in person three to five days per week and be based in the New York City area or within a reasonable commuting distance.
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.
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.
Don’t Meet Every Qualification Yet?
If you don’t meet every qualification for this role, we encourage you to apply to our
Forward-Deployed AI Engineer (In Training)
opportunity.
This role is designed for high-potential software engineers and full-stack developers who are building the production engineering, applied AI, and client-delivery skills required to become Forward-Deployed AI Engineers at Turing.
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: Canada Wide - Excluding Quebec; British Columbia
Workplace: Hybrid
ABOUT THE ROLE
Safe Software is looking for a Staff AI Engineer to design, build, and deploy production-grade AI systems across the organization.
This is a hands-on engineering role responsible for the full AI lifecycle, from data preparation and model development through evaluation, deployment, monitoring, and continuous improvement. You will work across generative AI, applied machine learning, retrieval, and agentic systems while establishing reusable architectures and engineering standards for complex production implementations.
ABOUT THE TEAM
AI Enablement helps Safe Software adopt AI effectively and responsibly. The team builds shared capabilities, platforms, and engineering standards while enabling departments to deliver AI solutions aligned with common security and governance practices.
WHAT YOU'LL BE DOING
- Design, build, evaluate, deploy, and operate end-to-end AI/ML systems in production, spanning data preparation, model development, training or fine-tuning, integration, application logic, monitoring, and continuous improvement.
- Architect and build agentic and multi-agent systems, including orchestration, task routing, shared state, tool use, agent handoffs, human oversight, and failure recovery.
- Design and build enterprise knowledge and retrieval systems across structured and unstructured data, using data pipelines, embeddings, hybrid search, reranking, metadata, and access-controlled retrieval.
- Integrate AI solutions with enterprise applications, APIs, databases, data platforms, and governed tools.
- Establish automated testing, evaluation, and observability practices covering task success, model and retrieval quality, hallucination risk, tool execution, safety, latency, cost, drift, and regression.
- Design secure and responsible AI systems with least-privilege access, auditability, sensitive-data protection, and safeguards against prompt injection, data leakage, and unauthorized actions.
- Create reusable architectures, libraries, and engineering standards, and provide cross-functional technical leadership through design reviews, mentoring, and stakeholder collaboration.
- Evaluate emerging Large Language Models, frameworks, and platforms and make evidence-based adoption recommendations.
QUALIFICATIONS, SKILLS, AND COMPETENCIES
WHAT WE'RE LOOKING FOR
- 8+ years across software engineering and AI/ML, including 3+ years building and operating AI/ML systems in production at scale.
- Strong software engineering skills, particularly in Python or comparable backend technologies.
- Experience developing, adapting, fine-tuning, evaluating, deploying, and monitoring AI or machine learning models.
- Applied AI experience in enterprise use cases such as chatbots, workflow automation, RAG, intelligent document processing, recommendation systems, or decision support.
- Strong understanding of generative AI, LLMs, retrieval systems, agent-based architectures, and applied machine learning.
- Experience with production data pipelines, APIs, model-serving infrastructure, testing, security, reliability, and observability.
- Ability to explain complex technical decisions and tradeoffs to engineering teams and business stakeholders.
NICE TO HAVE
- Experience with agent and workflow orchestration tools such LangGraph, Semantic Kernel, AutoGen, CrewAI, or equivalent.
- Experience with vector databases, semantic or hybrid search, embeddings, and reranking.
- Experience with platforms such as Databricks, Snowflake, Amazon Bedrock, Microsoft Foundry/Azure AI, or equivalent.
- Familiarity with MCP, A2A, self-hosted or open-weight models, and hybrid AI architectures.
WHAT YOU CAN EXPECT
When you choose a career with Safe Software, you’re also choosing…
- Meaningful Work: Make a profound impact across our business, workplace and data integration product.
- A Supportive Environment: Feel empowered to share your ideas and implement them with high autonomy and team support.
- Social Responsibility: Become part of a team that finds meaningful ways to give back https://www.safe.com/about/community-initiatives/. Take paid time off to volunteer for one of our Safe-organized opportunities that align with our core community initiatives.
- Learning & Career Development: We believe in your continuous learning and growth. Take advantage of an annual learning budget and training programs paid for by Safe.
- Flexible Working Hours: Flexible and remote-friendly work arrangements to fit your lifestyle. Work when you want, and how you want to.
- Work-Life Balance: There's no place for burnout at Safe. Maintain a healthy balance of your personal and work life without splitting yourself in two. Enjoy 3 weeks of vacation to recharge, plus an additional paid 6 seasonal days off per year.
- Health & Wellness: Extended health, dental, health or lifestyle spending, and counseling benefits from day 1. That’s right, no waiting period.
- Family is important: We are dedicated to supporting our employees through parenthood and offer a Parental Leave Top-Up Program for new parents through childbirth or adoption.
- Shared Success: Share in Safe’s success with our bi-annual profit sharing and RRSP/TFSA matching program.
- An Accessible Commute: Regardless of your commute method, we’re located close to public transit, and provide complimentary parking and bike storage for our team!
ABOUT SAFE SOFTWARE
Safe Software transforms organizations with FME, the only All-Data Any-AI Enterprise Integration Platform connecting all your data, anywhere, at any velocity.
With over 30 years of expertise and 25,000+ enterprise customers across 125+ countries, we simplify your data journey, wherever it leads.
Founded in 1993, Safe is headquartered in Surrey, BC with over 300 team members and counting. We’re always looking for talented individuals with diverse backgrounds who are determined to learn and grow. Are you ready to join the team?
OUR COMMITMENT TO DIVERSITY AND INCLUSION
Safe Software is an equal opportunity employer and we truly believe that innovation and strength begin with diversity and inclusion.
We welcome all candidates regardless of race, gender identity or expression, sexual orientation, age, ability, disability, national or ethnic origin, political belief, religion, or family status.
Should you require accommodations during the recruitment process, please contact hr_dept@safe.com.
NOTICE REGARDING USE OF AUTOMATED TOOLS IN HIRING
At Safe Software, we use automated tools to help us process applications and identify qualified candidates. These tools may assist in screening resumes and summarizing interview content based on the information you provide. This helps our team review applications efficiently while ensuring every candidate is considered based on the requirements of the role.
Please be assured that the final hiring decision is always made by a member of our team. For more information on how we protect your privacy, please see our policy https://www.safe.com/legal/#applicant-privacy-policy. If you have questions about this process, please contact us at hr_dept@safe.com.
Location: Ukraine
OUR HIRING PROCESS:
We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment.
We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team.
At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team.
From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live.
INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our
Privacy Policy
We're looking for Senior AI Engineers to design, build and run LLM-powered agents and AI features in production. You'll work across the full lifecycle: from scoping a use case with stakeholders, through architecture and development, to deployment, evaluation and ongoing improvement.
This is a hands-on role for engineers who think like product owners: you understand the business problem, define what success looks like in numbers, ship to real users, and own the result after launch.
Our stack: Python and TypeScript/Node.js, PostgreSQL, Kafka, Docker, GitHub Actions, AWS. We run multiple LLM providers (Anthropic, OpenAI, Google, AWS Bedrock and others) behind a shared LLM gateway, with MCP for tool access. We work AI-native: agentic coding tools are part of how engineering gets done here, and we provide official Anthropic Claude certification for our engineers.
As part of our team, your responsibilities in this role will include:
Design and build LLM agents and agentic workflows: tool use via MCP, structured outputs, retrieval (RAG), multi-step orchestration, human review steps where needed.
Build and maintain MCP servers and tool layers that give agents governed access to company data and systems.
Own quality and cost: evals and golden sets, per-agent telemetry (tokens, cost, latency, accuracy), prompt and model versioning, provider failover and model routing.
Ship through CI/CD like any other production service: tests and evals in the pipeline, containerized deploys, monitoring, rollbacks.
Contribute to shared platform pieces: the agent template, the LLM gateway, observability.
Work directly with business stakeholders to scope, prioritize and validate use cases. Push back when something doesn't need an agent.
Use AI coding tools daily. Claude Code is our default; deep experience with a comparable agentic tool also works. You drive the tool, verify its output and catch its mistakes.
Our ideal candidate possesses the following skills:
5+ years of software engineering experience, with production systems you've designed, shipped and supported.
Proven experience building LLM-based agents or agentic workflows that reached production with real users.
Hands-on experience with agent frameworks and SDKs: Claude Agent SDK, Claude Managed Agents, Pydantic AI, LangGraph or similar. You can also explain what you'd build without one.
Hands-on experience with MCP and RAG: you've built MCP servers or equivalent tool layers, and retrieval pipelines over real, messy data.
Experience with multiple LLM providers and with AWS Bedrock: model selection, routing, fallbacks, cost and rate-limit management.
Strong Python and SQL. Comfortable in TypeScript/Node.js.
Solid production engineering on AWS: Docker, CI/CD, testing, observability.
Product thinking and business focus: you start from the problem and its cost, define success in measurable terms, and own outcomes.
Daily use of agentic coding tools (Claude Code, Codex, Cursor or similar), with the judgment to verify what they produce.
Clear communication with technical and non-technical stakeholders, in English.
Nice to have:
LLM observability or gateway tooling (Langfuse, LiteLLM, OpenTelemetry for LLM traces or similar).
B2B contact and company data: enrichment, deduplication, matching.
Cloud operations or FinOps: monitoring, incident handling, cost management.
Event-driven or workflow-engine experience (Kafka, Temporal or similar).
Experience replacing no-code or workflow-tool automations with production code.
What we offer:
Fully remote work format;
A collaborative and creative environment that values initiative and experimentation;
Paid time off and sick leave;
Reduced working hours on Fridays during the summer;
Days-off on US national holidays + your birthday;
Schedule: 14 PM - 23 PM EEST (Kyiv time).
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.
WHAT YOU’LL DO
As an Agent Strategist https://sierra.ai/blog/agent-strategist-your-phd-in-applied-ai, you own how Sierra’s AI agents come to life for our customers — from first pilot to a production agent handling thousands of conversations a day. You sit at the intersection of product, building agents and customer-facing work, and stay just as close to the technology as you are to the people you build for. You transform a customer’s thorniest, highest-stakes problems into agents that measurably move their business.
- Own the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle. Take agents from initial scope through conversation design, tooling, and evaluation, to launch and continuous iteration in production — translating business goals into an agent that outperforms, and tuning relentlessly until it’s the best version of itself in the real world. You’ll have real ownership and autonomy over the outcome.
- Be the trusted strategic advisor to enterprise leaders. Sit shoulder-to-shoulder with our customers’ executives, understand what success actually means to their business, and shape the AI strategy that gets them there.
- Partner with the customer’s working teams day to day. Run working sessions, troubleshoot the agent as issues come up, and make the calls that keep the build on track for launch.
- Directly impact product. Surface unmet needs from your customer work, and feed them back to research and platform to shape where Sierra goes next.
EXAMPLE PROJECTS
These are the kinds of projects that strategists on our team have worked on recently:
- Scope and launch a subscription-retention agent for a large telecommunications or media company that consistently outperforms human agents at saving at-risk customers.
- Stand up an agent for a commerce customer that troubleshoots a broken device end-to-end and personalizes product recommendations in the same conversation.
- Redesign the conversation flows for a financial services agent so it can handle complex, regulated interactions — and convert a pilot into a multi-team production deployment. See our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services for examples.
- Partner with product on a net-new capability — a new agent architecture or self-service tooling — using a live customer as the design partner.
- Define the evaluation and quality bar for a new agent, then use those metrics to drive a measurable lift in outcome https://sierra.ai/blog/outcome-based-pricing-for-ai-agents week over week.
WHAT YOU’LL BRING
- Customer obsession. Genuine energy being in front of customers — understanding their business and needs, thriving in complex organizations, and building trusted relationships.
- Communication. Clear, direct, and persuasive across technical and non-technical audiences.
- Strategic problem-solving in ambiguity. Strong analytical and critical-thinking skills to break down complex problems, spot risks early, and adapt as things change fast.
- Technical aptitude. Comfortable engaging directly with technical concepts - reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in a design discussion.
- Ownership and delivery. A track record of running multiple complex, high-visibility projects at once and driving them to outcomes.
- Genuine interest in Financial Services and improving the end customer experience. Experience in financial technology, implementations at financial institutions, working inside of these institutions or familiarity with financial services security and compliance requirements (fair lending, PII handling, etc.) are a strong plus.
EVEN BETTER...
- Experience building or deploying AI/LLM agents in production — hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) — working closely with technical counterparts.
- You’ve been a founder, founding team member, or operator — you know how to balance craft, ownership, and speed.
- A degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience — and/or an MBA or comparable experience at the intersection of technology and business.
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.
Онлайн-сервис Гритис — персональный ассистент в сфере подарков и поздравлений, помогает формулировать индивидуальные поздравления и подбирать подарки-впечатления. Техническая часть (бэкенд на PHP/WordPress, RAG-модель, каркас чата) реализована и работает. Проект на этапе MVP, разовая проектная работа с возможными доработками.
Задачи:
— Разработка ультра-минималистичного Borderless-дизайна интерфейса диалогового окна чата в стиле Google Gemini (AI Mode), включая дизайн пузырей сообщений, многострочной зоны ввода, иконок управления и анимации ожидания ответа ИИ.
— Отрисовка премиального e-commerce контейнера для интерактивных карточек подарков с акцентом на цену, галерею, иконки триггеров и кнопки «Купить в 1 клик» и «Перейти к партнеру».
— Дизайн экрана быстрых ответов с интерактивными горизонтальными кнопками-чипсами для выбора параметров.
— Дизайн страницы каталога подарков с боковым AJAX-фильтром (совместимость с FacetWP) и поп-апа перенаправления на сайты партнеров.
Требования:
— Опыт UX/UI от 2-3 лет с портфолио аккуратных интерфейсов (чаты, личные кабинеты, мобильные приложения, e-commerce).
— Понимание веб-верстки, макеты должны легко переноситься на Elementor Pro.
— Работа в Figma по чистым компонентам, автолейаутам и стилям.
Условия:
— Разовая проектная задача с фиксированной оплатой, бюджет и сроки обсуждаются после предложения кандидата.
— При успешном выполнении возможен приоритет на долгосрочное сотрудничество с добавлением новых функций и кастомизацией персонажей.
После отклика кандидатам высылается полное техническое задание с описанием логики, шапкой сайта, брейкпоинтами адаптивности, размерами и требованиями к форматам экспорта графики (SVG, WebP, Lottie JSON).
Задачи:
— Руководить командой Computer Vision Engineers
— Проектировать архитектуру production AI-систем
— Менторить инженеров и проводить code review
— Декомпозировать задачи и контролировать качество реализации
— Разрабатывать пайплайны обработки десятков и сотен RTSP-потоков
— Оптимизировать инференс на GPU и CPU
— Принимать ключевые технические решения
— Участвовать в найме и развитии AI-команды
Основной стек:
Python, PyTorch, OpenCV, YOLO, RTSP, GStreamer, NVIDIA DeepStream, TensorRT, Triton Inference Server, ONNX, OpenVINO, CUDA, FastAPI/gRPC, Docker и Kubernetes.
Что важно:
✅ Сильный коммерческий опыт в Computer Vision и Video Analytics
✅ Опыт технического лидерства или менторства
✅ Запуск production AI-систем
✅ Уверенное знание Python, PyTorch, OpenCV и YOLO
✅ Практический опыт с RTSP, GStreamer, DeepStream и TensorRT
✅ Оптимизация моделей через ONNX, TensorRT, OpenVINO, CUDA или Quantization
✅ Понимание высоконагруженной обработки видеопотоков
✅ Умение принимать и аргументировать архитектурные решения
Будет плюсом:
➕ Triton Inference Server
➕ C++ и CUDA
➕ Kafka и потоковая обработка данных
➕ MLflow и MLOps
➕ ViT, DETR, Swin и Video Transformers
➕ VLM, RAG, LangGraph, vLLM и Function Calling
➕ Опыт найма и формирования AI-команд
Предлагаем влияние на архитектуру и технологический стек, сильную инженерную команду и работу над высоконагруженной системой промышленного уровня.
Задачи:
• Формировать AI-стратегию и roadmap бизнес-направления.
• Находить наиболее перспективные точки применения AI.
• Самостоятельно запускать первые прототипы и AI-пилоты.
• Быстро проверять гипотезы и показывать первые измеримые результаты.
• Создавать AI-агентов, RAG-решения и AI-автоматизации.
• Формировать и приоритизировать портфель AI-инициатив.
• Совместно с FDE и AI-командой доводить успешные пилоты до production и масштабирования.
• Переосмысливать бизнес-процессы с учетом возможностей AI.
• Работать с руководителями бизнес-направлений и защищать AI-инициативы.
• Следить за развитием AI-технологий и применять новые подходы в реальных бизнес-кейсах.
Требования:
• 7+ лет профессионального опыта в технологиях, AI/ML, разработке продуктов или digital transformation.
• Практический опыт запуска AI/ML или технологических продуктов.
• Сильное понимание LLM, Generative AI, AI Agents и RAG.
• Способность самостоятельно собрать работающий AI-прототип.
• Product mindset и ориентация на быстрый результат.
• Стратегическое мышление и способность формировать AI-roadmap.
• Умение связывать технологии с конкретным бизнес-эффектом.
• Опыт работы с руководителями и топ-менеджментом.
• Высокая самостоятельность и ответственность за результат.
AI-инструменты и технические навыки:
• Практический опыт работы с OpenAI, Claude, Gemini, Llama, Qwen или аналогичными LLM.
• Работа с LLM API, Prompt Engineering, Tool/Function Calling.
• Создание AI-агентов с использованием LangChain, LangGraph, LlamaIndex или аналогов.
• Практическое понимание RAG, embeddings, vector databases.
• Использование AI coding-инструментов: Codex, Cursor, Claude Code или аналогов.
• Python, REST API, SQL — на уровне, достаточном для самостоятельного создания прототипов.
• Опыт работы с n8n, Make или другими инструментами автоматизации.
• Понимание принципов работы и ограничений LLM, стоимости моделей и вопросов безопасности корпоративных данных.
Кого мы ищем:
• Не классического бизнес-аналитика или координатора.
• Нужен человек, который способен: понять бизнес → увидеть возможность применения AI → самостоятельно собрать первый пилот → показать результат → сформировать roadmap → масштабировать решение вместе с командой.
Главный результат:
• Быстрые первые победы и последующая системная AI-трансформация бизнес-направления.
Задачи:
— развивать и рефакторить оркестрацию агентов на LangGraph
— разрабатывать скиллы и инструменты (tools) для агента
— интегрировать LLM (писать и оптимизировать system/user-промпты, проектировать Pydantic-схемы для структурированного вывода, настраивать параметры моделей)
— подключать внешние системы (HTTP API, Kafka, поисковые движки)
— строить RAG-пайплайн
— покрывать код unit-тестами
— участвовать в проектировании архитектуры агентских систем.
Требования:
— опыт разработки AI агентов от 1 года
— опыт разработки python от 3 лет
— опыт с веб-фреймворками (FastAPI и/или aiohttp) и проектировали REST API; опыт работы с WebSocket/SSE для real-time коммуникаций
— опыт интеграции LLM через API (GigaChat, аналоги)
— опыт с LangGraph/LangChain или похожими оркестраторами агентов
— опыт с PostgreSQL (проектирование схем, миграции, транзакции) и асинхронным доступом к БД
— умеете доводить LLM-фичи до стабильной работы в проде.
Будет плюсом:
— опыт работы с AEF
— опыт с RAG
— опыт с Kafka и событийными интеграциями
— опыт работы с Docker / Kubernetes, Helm, CI/CD пайплайнами
— навыки работы с генеративными AI-моделями
— опыт создания AI-агентов и использования их в работе будет преимуществом
— опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов
— инструментальное владение AI для анализа, генерации и автоматизации.
Условия:
— гибридный формат работы (2-3 дня в офисе). Офис по адресу: г.Москва офис Кутузовский проспект 32
— ежегодный пересмотр зарплаты, квартальная и годовая премия
— корпоративный спортзал и зоны отдыха
— более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
— программа адаптации и помощь руководителя на старте
— 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.
Задачи:
— Находить боли в процессах продаж, производства, закупок и тендеров, где ИИ может дать быстрый эффект.
— Ставить задачи с определением входных и выходных данных, критериев готовности, метрик успеха и границ.
— Делать решения с помощью Claude: создавать промпты, пайплайны, при необходимости использовать RAG, работать с данными и API, интегрировать с CRM, телефонией и почтой.
— Внедрять решения на сервере, проверять на боевых данных, следить за качеством и стоимостью.
— Обучать пользователей, объяснять и снимать сопротивление для реального использования инструментов.
— Переключаться между проектами, например, сводка по звонкам или помощник по тендерам.
Требования:
— Опыт аналитика, продакта или AI-инженера от примерно 2 лет с доведением задач до результата.
— Практический опыт создания решений с помощью ИИ (Claude, ChatGPT, Cursor), включая автоматизацию, ботов, скрипты, интеграции.
— Навыки промпт-инжиниринга и понимание работы LLM, их возможностей и ограничений.
— Умение читать и править Python, работать с API и писать простой SQL.
— Знания Linux и Docker: работа с консолью, контейнерами, развёртыванием сервисов, чтение логов.
— Грамотный русский язык и умение понятно объяснять как бизнесу, так и техническим специалистам.
Будет плюсом:
— Программирование сверх базового уровня.
— Опыт с RAG и векторными базами данных.
— Знание n8n, Make, LangChain.
— Опыт с речевой аналитикой.
— Опыт работы с Odoo, 1С, CRM, телефонией.
— Понимание 152-ФЗ и работы с персональными данными.
Условия:
— Работа в команде с архитектором и аналитиками, прямой доступ к заказчикам.
— AI-first среда с ежедневным использованием Claude, собственным сервером разработки и песочницей для экспериментов без согласования.
— Реальное влияние: инструменты внедряются в продакшн и используются подразделениями группы.
— Возможности роста до ведущего AI-аналитика или владельца направления AI-продуктов.
Задачи:
— разработка LLM агентов
— создание логики работы и взаимодействия агентов
— дообучение NLP моделей
— создание RAG систем
— вывод и сопровождение моделей
— написание API для выводимых моделей.
Требования:
— знания в области математики, data science
— владение Python (pandas, numpy, torch, fastapi, langchain, etc)
— знание SQL, spark
— приветствуется опыт работы с git, docker
— опыт работы с NLP пайплайнами.
Условия:
— комфортный современный офис рядом с м. Кутузовская
— возможность выбрать удобный график – офис/гибрид
— ежегодный пересмотр зарплаты, квартальная и годовая премия (премия указывается в зависимости от должности и системы премирования)
— корпоративный спортзал и зоны отдыха
— более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
— программа адаптации и помощь руководителя на старте (для вакансий уровня Junior)
— расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа
— гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
— подписка Прайм с возможностью совместного использования на трёх близких
— вознаграждение за рекомендацию друзей в команду Сбера.
Задачи:
— Разработка от исследования до прода, включая совместную с командой проработку архитектуры, выбор подходов и библиотек, декомпозицию задач.
— Поддержка и развитие существующей кодовой базы: рефакторинг, оптимизация производительности, устранение техдолга.
— Code review, менторинг junior-разработчиков.
— Быстрое прототипирование новых идей и концептов (PoC / MVP).
— Реализация пилотных интеграций: сторонние сервисы, AI API, новые UI-паттерны.
— Настройка A/B-тестов и feature flags для валидации гипотез на реальных пользователях.
— Сбор и анализ метрик по результатам пилотов — формирование выводов для принятия решений о масштабировании.
— Итеративная доработка пилотов до production-ready состояния при положительных результатах.
Требования:
— Коммерческий опыт frontend-разработки от 5+ лет.
— Отточенный навык писать чистый и поддерживаемый код с соблюдением стандартов кодирования.
— Продвинутые знания и практический опыт работы с TypeScript.
— Глубокое понимание React и его экосистемы.
— Уверенный опыт адаптивной и кроссбраузерной вёрстки.
— Опыт декомпозиции на переиспользуемые компоненты и модули.
— Понимание паттернов проектирования (композиция, HOC, render props, compound components).
— CI/CD — понимание пайплайнов, деплоя фронтенда.
Будет плюсом:
— Знание основ Docker/Docker Compose/K8n.
— Опыт с дизайн-системами и компонентными библиотеками (Storybook).
— Понимание основ UX/UI.
— Опыт использования AI-ассистентов для разработки (Claude Code, GitHub Copilot, Cursor).
— Понимание возможностей LLM API (OpenAI, Anthropic) и опыт интеграции в продукт.
— Знакомство с RAG-паттернами, embeddings, vector databases.
— Опыт создания AI-powered фич в пользовательских интерфейсах (чат-боты, автокомплит, генерация контента).
Условия:
— Оформление в соответствии с ТК РФ (ТД или ИП).
— Формат работы: удаленно, с возможностью посещения офиса в Москве для получения техники и решения проблем с оборудованием.
— Своевременная заработная плата, выплачивается 2 раза в месяц, сумма обсуждается на собеседовании.
— График 5/2 с 9:00 до 18:00; выходные — суббота и воскресенье.
— ДМС и стоматология после испытательного срока.
— Предоставление техники (MacBook).
— Компания входит в список IT лицензированных аккредитованных компаний.
— Отсутствие бюрократии, прозрачность, быстрое принятие решений, уважение к каждому члену команды.
— Поддержка в значимых событиях.
УдалённоseniorГеография найма не уточнена, офис: Москва
Задачи:
— Переводить бизнес-задачи в архитектурные и технические решения
— Развивать AI-продукты, интеграции, новые каналы и источники данных
— Определять затрагиваемые компоненты, API, контракты, модели данных и бизнес-семантику
— Декомпозировать разработку на проверяемые задачи для AI coding agents
— Проверять сгенерированный код, проводить code review, тестирование и выпуск изменений
— Отвечать за стабильность, безопасность и конечный результат
Требования:
— Опыт промышленной разработки от 3 лет
— Бэкграунд в аналитике данных, BI или системном анализе
— Умение работать с бизнес-требованиями, метриками, моделями данных и интеграционными контрактами
— Практический опыт промпт-инжиниринга: проектирование, тестирование и оптимизация промптов для LLM, построение многошаговых AI-флоу и достижение стабильного качества ответов
— Практический опыт с LLM, AI-агентами, RAG, tool calling, structured outputs и MCP
— Уверенное знание TypeScript или Python, API, SQL, Git, CI/CD и автоматизированного тестирования
— Понимание принципов работы современных языковых моделей, ограничений LLM и способов повышения качества генерации
— Системное мышление, самостоятельность и ответственность за продукт целиком
Будет преимуществом:
— Опыт создания и оптимизации сложных промптов для различных AI-сценариев (reasoning, extraction, generation, classification)
— Опыт создания evals, guardrails и контроля качества AI-ответов
— Опыт работы с React, Telegram-ботами, BI-платформами и семантическими слоями
Условия:
— Конкурентную заработную плату (обсуждается индивидуально)
— Профессиональный рост и участие в масштабных проектах
— Работу в крупном холдинге с активной цифровой трансформацией
— Сильную ИТ-команду и поддержку руководства
— Необходимость краткосрочного приезда в солнечный Ташкент для оформления
УдалённоmiddleГеография найма не уточнена, офис: Ташкент
Задачи:
— Переводить бизнес-задачи в архитектурные и технические решения
— Развивать AI-продукты, интеграции, новые каналы и источники данных
— Определять затрагиваемые компоненты, API, контракты, модели данных и бизнес-семантику
— Декомпозировать разработку на проверяемые задачи для AI coding agents
— Проверять сгенерированный код, проводить code review, тестирование и выпуск изменений
— Отвечать за стабильность, безопасность и конечный результат
Требования:
— Опыт промышленной разработки от 3 лет
— Бэкграунд в аналитике данных, BI или системном анализе
— Умение работать с бизнес-требованиями, метриками, моделями данных и интеграционными контрактами
— Практический опыт промпт-инжиниринга: проектирование, тестирование и оптимизация промптов для LLM, построение многошаговых AI-флоу и достижение стабильного качества ответов
— Практический опыт с LLM, AI-агентами, RAG, tool calling, structured outputs и MCP
— Уверенное знание TypeScript или Python, API, SQL, Git, CI/CD и автоматизированного тестирования
— Понимание принципов работы современных языковых моделей, ограничений LLM и способов повышения качества генерации
— Системное мышление, самостоятельность и ответственность за продукт целиком
Будет преимуществом:
— Опыт создания и оптимизации сложных промптов для различных AI-сценариев (reasoning, extraction, generation, classification)
— Опыт создания evals, guardrails и контроля качества AI-ответов
— Опыт работы с React, Telegram-ботами, BI-платформами и семантическими слоями
Условия:
— Конкурентную заработную плату (обсуждается индивидуально)
— Профессиональный рост и участие в масштабных проектах
— Работу в крупном холдинге с активной цифровой трансформацией
— Сильную ИТ-команду и поддержку руководства
— Необходимость краткосрочного приезда в солнечный Ташкент для оформления
УдалённоmiddleГеография найма не уточнена, офис: Ташкент
Location: Poland
OUR HIRING PROCESS:
We will review your application against our job requirements. We do not employ machine learning technologies during this phase as we believe every human deserves attention from another human. We do not think machines can evaluate your application quite like our seasoned recruiting professionals—every person is unique. We promise to give your candidacy a fair and detailed assessment.
We may then invite you to submit a video interview for the review of the hiring manager. This video interview is often followed by a test or short project that allows us to determine whether you will be a good fit for the team.
At this point, we will invite you to interview with our hiring manager and/or the interview team. Please note: We do not conduct interviews via text message, Telegram, etc. and we never hire anyone into our organization without having met you face-to-face (or via Zoom). You will be invited to come to a live meeting or Zoom, where you will meet our INFUSE team.
From there on, it’s decision time! If you are still excited to join INFUSE and we like you as much, we will have a conversation about your offer. We do not make offers without giving you the opportunity to speak with us live.
INFUSE is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our
Privacy Policy
We're looking for Senior AI Engineers to design, build and run LLM-powered agents and AI features in production. You'll work across the full lifecycle: from scoping a use case with stakeholders, through architecture and development, to deployment, evaluation and ongoing improvement.
This is a hands-on role for engineers who think like product owners: you understand the business problem, define what success looks like in numbers, ship to real users, and own the result after launch.
Our stack: Python and TypeScript/Node.js, PostgreSQL, Kafka, Docker, GitHub Actions, AWS. We run multiple LLM providers (Anthropic, OpenAI, Google, AWS Bedrock and others) behind a shared LLM gateway, with MCP for tool access. We work AI-native: agentic coding tools are part of how engineering gets done here, and we provide official Anthropic Claude certification for our engineers.
As part of our team, your responsibilities in this role will include:
Design and build LLM agents and agentic workflows: tool use via MCP, structured outputs, retrieval (RAG), multi-step orchestration, human review steps where needed.
Build and maintain MCP servers and tool layers that give agents governed access to company data and systems.
Own quality and cost: evals and golden sets, per-agent telemetry (tokens, cost, latency, accuracy), prompt and model versioning, provider failover and model routing.
Ship through CI/CD like any other production service: tests and evals in the pipeline, containerized deploys, monitoring, rollbacks.
Contribute to shared platform pieces: the agent template, the LLM gateway, observability.
Work directly with business stakeholders to scope, prioritize and validate use cases. Push back when something doesn't need an agent.
Use AI coding tools daily. Claude Code is our default; deep experience with a comparable agentic tool also works. You drive the tool, verify its output and catch its mistakes.
Our ideal candidate possesses the following skills:
5+ years of software engineering experience, with production systems you've designed, shipped and supported.
Proven experience building LLM-based agents or agentic workflows that reached production with real users.
Hands-on experience with agent frameworks and SDKs: Claude Agent SDK, Claude Managed Agents, Pydantic AI, LangGraph or similar. You can also explain what you'd build without one.
Hands-on experience with MCP and RAG: you've built MCP servers or equivalent tool layers, and retrieval pipelines over real, messy data.
Experience with multiple LLM providers and with AWS Bedrock: model selection, routing, fallbacks, cost and rate-limit management.
Strong Python and SQL. Comfortable in TypeScript/Node.js.
Solid production engineering on AWS: Docker, CI/CD, testing, observability.
Product thinking and business focus: you start from the problem and its cost, define success in measurable terms, and own outcomes.
Daily use of agentic coding tools (Claude Code, Codex, Cursor or similar), with the judgment to verify what they produce.
Clear communication with technical and non-technical stakeholders, in English.
Nice to have:
LLM observability or gateway tooling (Langfuse, LiteLLM, OpenTelemetry for LLM traces or similar).
B2B contact and company data: enrichment, deduplication, matching.
Cloud operations or FinOps: monitoring, incident handling, cost management.
Event-driven or workflow-engine experience (Kafka, Temporal or similar).
Experience replacing no-code or workflow-tool automations with production code.
What we offer:
Fully remote work format;
A collaborative and creative environment that values initiative and experimentation;
Paid time off and sick leave;
Reduced working hours on Fridays during the summer;
Days-off on US national holidays + your birthday;
Schedule: 14 PM - 23 PM EEST (Kyiv time).
Задачи:
• Проектирование и разработка сложных Агентных и AgenticRAG систем. Обеспечение воспроизводимости и отказоустойчивости
• Разработка решений начиная от прототипа, заканчивая выводом в промышленную эксплуатацию
• Определение ML SysDes решения с учетом разрешенного технологического стека
• Участие в валидации и автомониторинге моделей, проведение A/B тестирования
Требования:
• Высшее образование в сфере компьютерных наук, физ-мата, прикладной математики и информатики. Приветствуются дипломы ведущих технических и научных ВУЗов (МФТИ, МГУ, Сколтех, ВШЭ, ИТМО, МИФИ и др.)
• Знание мат. статистики, классического ML, NLP, опыт в постановке и интерпретации экспериментов
• Опыт e2e-разработки ML/AI-пайплайнов (в т.ч. RAG-пайплайнов) и проектировании архитектуры AI решений
• Умение переводить бизнес-постановку задачи в ML-постановку
• Высокий уровень владения Python и SQL
• Знание фреймворков, библиотек, алгоритмов машинного обучения: XGBoost, CatBoost, PyTorch, TensorFlow, Transformers
• Знание принципов построения RAG, VisionRAG и AgenticRAG систем
• Знание архитектур нейронных сетей: RNN, LSTM, трансформеры (BERT, BART, T5)
• Знание агентных архитектур (ReAct, Multi-agent и др.)
• Знание фреймворков для работы с LLM (LangChain, LangGraph и др.)
• Знание веб-фреймворков (FastAPI, Flask), контейнеризации (Docker)
• Понимание жизненного цикла моделей (CRISP-DM)
Условия:
• Гибкий гибрид (обсуждаем индивидуально)
• Современный IT-офис вблизи Москва-Сити с фитнес-залом
• Ипотека с выгодой для сотрудника и льготные условия кредитования
• Бесплатная подписка СберПрайм+
• Скидки на продукты компаний-партнеров
• ДМС с первого дня и льготное страхование для близких
• Корпоративная пенсионная программа
• Обучение за счет компании: онлайн курсы в онлайн-школе Сбера и неограниченный доступ к библиотеке, обучение в Корпоративном университете, тренинги, митапы и возможность получить новую квалификацию
• Крупнейшее DS&AI Community — более 600 DS банка, регулярный обмен знаниями, опытом и лучшими практиками, интерактивные лекции и мастер-классы от ведущих ВУЗов и экспертов технологических компаний, дайджест о самых последних разработках в области DS&AI и отчеты с крупнейших конференций мира
Location: Distributed
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 Locations
Germany
Responsibilities
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.
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.
This role may require travel up to 20–50% to attend customer meetings, conferences, industry events, and in-person team collaboration.
Desirable Skills, Knowledge, and Experience
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.
Business Fluency in German
Bonus Points
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.
Compensation
For Germany based hires: Estimated annual salary is between €116,000 - €182,000.
This role is eligible to earn incentive compensation under Cloudflare's Sales Compensation Plan. The estimated annual salary range includes the on-target incentive compensation that may be attained in this role under the Sales Compensation Plan.
Equity: This role is eligible to participate in Cloudflare's equity plan.
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.
New York, New York, United States; For applicants from the European Union, please review
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