Location: Barcelona, Spain
Workplace: hybrid
⛵ About our Crew
Click&Boat
is a rental platform product of
Boats Group,
the fastest-growing digital business in the recreational boating space. We are a talented team of techies, creatives, marketers, closers and customer advocates who spend each day pushing the boundaries of technology to make buying, selling & renting boats easy. We spend each day surrounded by 500,000 boats from across the globe!
Click&Boat is the European leader in boat rentals
. Our marketplace makes boating accessible around the world, from a day trip to a week-long adventure, while enabling private and professional boat owners to generate additional income through rentals.
To support this growth, we are hiring a
Customer Experience Agent
to join a dynamic team in our Barcelona office and continue building a world-class, creative organization by finding the best talent for our incredible culture.
🚤 The role
In Click&Boat, there are 3 main operational Business Units :
Supply:
deals with boat owners and make sure the boats available on our platform generate revenues with the highest quality of service.
Sales:
deals with tenants and supports them all along a booking process, from quotations to closing the deal.
Customer Care:
represents the point of contact for our customers after a booking is closed by the Sales team (before, during and after the trip), and makes the link between boat owners and tenants (booking modification or cancellation, insurance or accident issues, etc).
As Customer Experience, you will integrate the Customer Care crew
and will play a key part in
supporting our users
, and collaborating closely with
the Finance, Sales and Supply crew members
across teams to deliver a high-quality work.
If you're excited about marketplaces, digital business and dynamic environments, you might be exactly who we’re looking for.
🛟 What floats your boat
As a central part of our day-to-day operations, your main mission will be to
handle customer interactions efficiently
, managing
service-related issues, complaints, and claims
between boat owners and renters. While your work will focus on r
esolving tickets
and ensuring smooth communication, you will also contribute to
maintaining our service quality
standards and
supporting seasonal team members
during the high season.
Operations (80%)
Low season (October - March)
Manage
incoming inquiries
from boat owners and renters via
tickets and phone calls
.
Provide
accurate and timely responses
, ensuring issues are properly documented and resolved.
Handle
routine requests
, updates, and follow-ups to maintain a high level of customer satisfaction.
High season (April - September)
Act as an
escalation point
for
complex or urgent cases
, managing communication via
email (80%)
and
phone (20%)
.
Mediate disputes
between boat owners and renters, investigating claims and
negotiating fair solutions
in line with Click&Boat’s
terms and conditions
.
Manage
critical cases
such as
last-minute cancellations, service complaints, or boat damage
, ensuring efficient resolution and clear communication between all parties.
Report recurring issues or feedback
to help improve our internal processes and overall service quality.
Internal process analysis and update (10%)
Prepare for
high-season operations
by coordinating seasonal staff training, onboarding, and analyzing end-of-season KPIs to enhance future processes.
Identify opportunities for
product and process improvements
, creating reports on user feedback and system bugs to support development teams.
Collaborate with
cross-functional teams
to optimize workflows and contribute to the global mission of reducing contact ratios and improving response times
Contribute to seasonal operations by helping prepare
training
materials, supporting
onboarding
sessions, and assisting temporary staff during the high season
Coaching and Quality Review (10%)
During high season (April-September), guide and support seasonal employees, conducting
quality reviews
and leading training sessions to uphold service excellence
🧭 What you bring aboard
We’re seeking motivated, detail-oriented team players with a passion for problem-solving and a knack for delivering excellent service.
Language Skills:
Bilingual in
French
and fluent in English.
Customer Experience:
1+ years of previous experience in customer-facing roles is required, handling legal complaints and complex users conflicts.
Solution-Oriented:
Comfortable handling challenging situations and finding creative resolutions.
Time Management Skills:
Demonstrated ability to prioritize tasks effectively, meet deadlines, and handle multiple responsibilities in a fast-paced environment.
Organized and Flexible:
Thrives in a dynamic environment, especially during high-season periods with weekend shifts.
Process-oriented and methodical:
enjoys following structured workflows and continuously improving efficiency in daily operations.
Queue management mindset:
takes satisfaction in maintaining a clean, organized ticket queue and ensuring no requests remain unresolved
🌊 Bonus points (great to have, never a dealbreaker)
Language skills: Any other language spoken from our markets is a plus (Spanish/Italian/German).
Passion for Boating:
An interest in boating or a connection to our industry is a bonus!
🗺 The hiring journey
Intro call with Talent Acquisition
Case Study
Interview with your future manager
Interview with the Head of Customer Care
We aim to keep things smooth, transparent, and respectful of your time throughout the process.
What awaits you aboard
🚀 A fast-growing international company with real impact;
💻 Remote work policy: 1 day per week, depending on periods of the year and seniority;
🌴 5 additional days off;
📖 Extensive internal training;
🥪 Lunch vouchers (Cobee);
💪 Gym partnerships (Wellhub);
🚤 Boat licence offered and exclusive discounts on your next boat trips;
🥐 Breakfast every Tuesday morning;
🌊 A welcoming office in Barcelona, next to the centrally located Cathedral and just a 20-minute walk from the sea;
🎉 Team-building activities.
Contract: Full-time, permanent.
🪝 Ready to join?
If this opportunity sounds like your next adventure, hit the “apply to this job” bottom.
Remember, even if you don’t meet every requirement, you might still be a great match for us! And yes, we’re especially talking to women here: science says that you are less likely to apply if you don’t meet them all. So go for it, we’d love to hear from you.
At Click&Boat, every application is reviewed with equal care and attention, regardless of age, gender, origin, disability, religion, sexual orientation, or any other characteristic. We hire for talent, drive, and mindset. The sea is open to all. 🌊
Location: Athens
Workplace: Remote
About the company:
KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe.
About the role
We are looking for an ML Engineer to improve the agent and long-context LLM capabilities behind Kiefer Tech’s AI products. You will work hands-on across post-training, data, evaluation, agent design, and inference, with the goal of making multi-step tasks more reliable in production.
What you will do
- Run post-training experiments using supervised fine-tuning, preference optimization, reinforcement learning, or other suitable methods.
- Improve how agents plan, use tools, manage execution, and recover from errors.
- Build benchmarks, verifiers, and diagnostic tools to measure agent performance and identify failures.
- Generate and curate training data, including agent trajectories and difficult cases from target workflows.
- Evaluate and improve long-context behavior, memory and retrieval interactions, and reliability over multi-step tasks.
- Work with ML, Product, and Engineering to improve inference and bring successful experiments into production with clear regression checks.
What you will need
- 3+ years of relevant ML or research engineering experience, with clear technical ownership and measurable results.
- Hands-on LLM post-training experience in at least one area: supervised fine-tuning, preference optimization, reinforcement learning, or a comparable method.
- Experience building agent systems involving tool use, multi-step execution, and error recovery.
- Strong skills in model and agent evaluation, failure analysis, and the creation or curation of training data.
- Strong Python, hands-on experience with PyTorch, JAX, TensorFlow, or a similar framework, and solid software engineering skills.
- Experience improving or deploying model-backed systems, with an understanding of LLM inference performance and cost.
Nice to have
- Reward modeling or verifier-based training.
- Long-context training, memory systems, retrieval, or context compression.
- Distributed training or high-performance LLM serving.
- Experience delivering agents for complex enterprise, coding, or research workflows.
What is there for you
- Compensation: Competitive package aligned with talent benchmarks.
- Impact: Hands-on work shaping AI capabilities for Kiefer Tech’s products and real-world applications.
- AI-native environment: Real challenges across model development, evaluation, and production AI systems.
- Culture: Engineering-first, high autonomy, low bureaucracy, and space to shape meaningful AI products.
Location: London
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.
Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace.
WHAT YOU’LL DO
- Design and deliver production-grade AI agents https://sierra.ai/blog/meet-the-ai-agent-engineer: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce.
- Drive the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way.
- Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups in Silicon Valley, embedding AI agents across their entire business stack to drive innovation and efficiency.
- Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product.
EXAMPLE PROJECTS
These are some examples of projects that engineers on our team have worked on recently:
- Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churn
- Develop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendations
- Create generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services!
- Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent development
- Experiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customers
WHAT YOU'LL BRING
- Experience building and scaling end-to-end production systems
- Strong technical problem-solving skills, especially in fast-changing, ambiguous environments
- A builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and ship
- Comfort working directly with customers to understand their needs and solve real-world problems
- Excellent communication skills - clear, direct, and persuasive across technical and non-technical audiences
EVEN BETTER...
- Experience building or deploying AI/LLM systems in production
- Have been a founder or founding engineer - you know what it means to balance craft, ownership, and speed
- Familiarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineering
- Prior experience with React, TypeScript, and/or Go
- Previous roles where you interfaced with customers or led technical projects with external stakeholders
OUR VALUES
- Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.
- Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.
- Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.
- Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.
- Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.
WHAT WE OFFER
We want our benefits to reflect our values and offer the following to full-time employees:
- Flexible (unlimited) paid time off
- Medical, dental, and vision benefits for you and your family
- Life insurance and disability benefits
- Retirement plan dependent on country of employment
- Parental leave
- Fertility and family building benefits through Carrot
- Lunch, as well as delicious snacks and coffee to keep you energized
- 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 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 even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
Location: Amsterdam, Netherlands
Are you comfortable navigating complex software systems, working with coding agents, and defining what makes developer tools actually useful? Do you want to shape how developers and AI work together inside IDEs?
About JetBrains
We create intelligent software development tools for developers and teams. More than 15 million users, over 300,000 companies, and 88 of the Fortune Global Top 100 rely on our products to solve real, complex problems. Our mission is simple: make development teams more productive and AI adoptable at scale.
What you’ll do
Agentic development is changing how software gets built. Developers no longer just chat with AI – they delegate tasks, run parallel agent sessions, and steer autonomous changes. As agents take on more work, reviewing and owning the output is becoming the hardest part of the process.
JetBrains Air is our open system for agentic development. It brings tools like Codex, GitHub Copilot, Claude Agent, Gemini, and Junie directly into JetBrains IDEs, providing an agentic-first user experience.
We are looking for a Senior Product Manager to lead key areas of Air. You’ll take ownership of high-impact workflows, work closely with cross-functional teams (including software engineers, designers, ML researchers, analysts, DevRel, and product marketing), and turn technical complexity into clear product direction.
Day to day, you will:
Take end-to-end ownership of key parts of Air in JetBrains IDEs, driving work from problem framing and discovery to delivery, adoption, and iteration.
Define and refine core agentic workflows, including task delegation, session monitoring, steering, and code review.
Model complex user flows, system states, permissions, and integration schemes to guide engineering and design decisions.
Maintain a transparent roadmap that balances quick improvements with long-term strategic investments.
Define telemetry, design experiments, analyze product data, and make evidence-based roadmap decisions.
Study how developers interact with leading AI agents and tools to inform product priorities.
Engage with the Agent Client Protocol (ACP) ecosystem and collaborate with partners building on it.
Partner with enterprise sales and support teams to address governance, privacy, and control requirements.
What you’ll bring
A systems-thinking mindset that easily breaks down complex architectures, workflows, and dependencies.
A data-driven approach to product decisions, including hands-on experience querying and analyzing telemetry.
Active personal experience using coding agents and clear perspectives on where current AI tools succeed and fail.
Strong product intuition for complex technical user experiences and developer workflows.
Clear, concise, and collaborative communication skills with the ability to explain complex technical concepts simply and build alignment across diverse groups of stakeholders.
Comfort navigating fast-changing technical landscapes with high ambiguity.
What you’ll need
Proven experience shipping end-user products as a product manager or in a similar role.
Strong technical grounding in software development workflows, including IDEs, git, code review, CI/CD, and package management.
A hands-on technical background sufficient to collaborate closely with software and ML engineers.
An understanding of core AI and agent concepts, including tool use, protocols (MCP/ACP), context retrieval, evaluations, and latency/cost trade-offs.
The ability to write SQL or Python to analyze product metrics and experiment results independently.
Fluency in English, both written and spoken.
What success looks like
In your first 6 to 12 months, success in this role means:
Driving measurable growth in active Air users and improving weekly/monthly retention (D7/D30).
Increasing agent session completion rates and the proportion of agent-generated changes accepted by developers.
Establishing clear, telemetry-backed decisions across your product roadmap areas.
Delivering validated product hypotheses consistently each quarter.
Contributing directly to JetBrains AI revenue growth and overall IDE value.
Why join JetBrains?
Strong base salary – We offer competitive pay that reflects your skills and experience.
Flexible work schedule – Enjoy the freedom to work from home or from the office.
Extra time off – More days to relax, recharge, and do the things you love.
Learning and development opportunities – Access to conferences, courses, and language classes.
Free meals and snacks – Lunch and refreshments provided to keep you fueled.
Health and wellness – On-site gyms or sports club stipends.
Internal events – Company-wide celebrations and team gatherings.
We are an equal opportunity employer. We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
If this sounds like a challenge you'd enjoy, send us your resume and a short note on why you're interested in Air.
#LI-KL1
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the
Recruitment Privacy Policy.
📌 Разработка инструментов для агентов и интеграций с корпоративными системами (1С, почта, файловые ресурсы). 📌 Обработка документов: договоры, счета, таблицы.
Location: Москва
Мы — команда в Департаменте маркетинга Сбера. Мы строим ИИ-агентов на базе LLM, совмещая скорость стартапа с масштабом большой компании: у нас есть доступ к огромным массивам данных, серьёзная инфраструктура и свобода выбирать лучшие инструменты под задачу.
Наши агентные направления Вы будете развивать ключевое направление департамента — создавать агентные системы двух типов:
1. Внутренние продукты для сотрудников. Автоматизация рабочих процессов внутри банка. Например, агенты, которые по текстовому брифу генерируют готовую структуру веб-страниц с контентом и изображениями, экономя время маркетинговых команд.
2. Внешние интерфейсы для клиентов. Диалоговые ассистенты на публичных ресурсах. Ваш код будет напрямую взаимодействовать с миллионами пользователей сайта Сбербанка, помогая им получать ответы через GigaChat, поиск по базам знаний (RAG) и систему скиллов.
Наш главный продукт сегодня — backend AI-ассистента на сайте банка. Это сложная система оркестрации диалогов на LangGraph.
Сейчас мы собираем современный агентный стек с нуля (LangGraph, RAG, function calling).
Первый этап отбора на эту вакансию — общение с AI-рекрутером. После отклика ждите сообщение от него, диалог займёт примерно 10 минут. Задача AI-рекрутера — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. AI-рекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным для всех!
Обязанности
* под руководством ментора разрабатывать и поддерживать оркестрацию агентов на LangGraph: реализовывать узлы графа, работать с состоянием и условными переходами
* писать и улучшать скиллы и инструменты (tools) для агента: интеграция с внешними HTTP API, валидация результатов по JSON Schema, простые ReAct-подграфы
* работать с LLM: писать и править промпты, проектировать Pydantic-схемы для структурированного вывода, экспериментировать с параметрами моделей и function/tool calling
* разрабатывать HTTP-контур: REST- и SSE-эндпоинты (инициация диалогов, стриминг ответов, управление историей) под руководством старших коллег
* участвовать в подключении внешних систем: HTTP API, Kafka, поисковые движки; помогать в развитии RAG-пайплайна (эмбеддинги, поиск, реранкинг)
* покрывать код тестами: unit- и интеграционные тесты (pytest, моки LLM и внешних сервисов); соблюдать стандарты качества — строгая типизация mypy, линтинг ruff, код-ревью
* участвовать в код-ревью (сначала как автор, затем как ревьюер), учиться архитектуре агентских систем и банковским требованиям к безопасности
* версионировать и проверять промпты: сравнение поведенческих сценариев, проверка на реальных моделях.
Требования
* уверенно пишете на Python (3.10+): знаете ООП, структуры данных, базовые алгоритмы; пишете чистый и читаемый код
* имеете практический опыт async/await / asyncio (коммерческий, стажировка или серьёзный пет-проект)
* знакомы с веб-фреймворками FastAPI и/или aiohttp на уровне pet-проектов или коммерческого опыта до 1–2 лет; понимаете основы REST API
* понимаете, как работают LLM через API (GigaChat, ChatGPT и аналоги): промпты, структурированный вывод, function/tool calling — хотя бы на уровне собственных экспериментов
* знакомы с LangChain/LangGraph или другими оркестраторами агентов либо готовы быстро освоить их при сильной инженерной базе
* знаете SQL и имеете базовый опыт работы с PostgreSQL (запросы, простые схемы, транзакции)
* используете Pydantic (или аналогичные инструменты валидации) и понимаете ценность строгой типизации
* готовы писать тесты (pytest), пользоваться Git, следовать стандартам код-ревью и CI/CD
* высокая обучаемость, curiosity к LLM-технологиям и желание расти в AI-инженерии
* начала высшего образования достаточно; рассматриваем студентов старших курсов и выпускников.
Будет плюсом:
-------------
* стажировки или коммерческий опыт разработки на Python (от 3–6 месяцев)
* пет-проекты с LLM: телеграм-боты с AI, RAG-ассистенты, агентные приложения на LangChain/LangGraph
* понимание RAG: эмбеддинги, векторный поиск, pgvector
* базовые навыки Docker, Git, Linux
* опыт работы с кодинговыми агентами (GigaCode CLI) и понимание принципов SDD
* знакомство с Kafka, OpenSearch, наблюдаемостью (Grafana/Prometheus, OpenTelemetry)
* участие в хакатонах, олимпиадах, open-source
* понимание основ безопасности и интерес к банковскому домену
* 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.
под руководством ментора разрабатывать и поддерживать оркестрацию агентов на LangGraph: реализовывать узлы графа, работать с состоянием и условными переходами. писать и улучшать скиллы и инструменты (tools) для агента: интеграция с внешними HTTP API, валидация результатов по JSON Schema, простые ReAct-подграфы.
Location: United States
Workplace: Remote
As an Engineering Manager on Coder’s Agentic Engineering team, you’ll lead engineers building and evolving the systems behind our agentic development experience. You’ll help make agents more capable, reliable, and useful across real development environments.
You’ll guide technical direction, grow the team, and keep execution sharp. You’ll work closely with Engineering, Product, and Design across the agent harness, integrations, and developer workflows.
This position is required to be in the US Eastern Time Zone.
WHAT YOU’LL DO HERE
- Lead and grow a team within our Agentic Engineering organization.
- Set technical direction across the agent harness, integrations, and workflows.
- Stay close to the code and contribute to architecture and implementation decisions.
- Evolve agent execution, tool use, context management, streaming, and long-running workflows.
- Extend our provider-agnostic architecture as models and capabilities change.
- Partner with Product and Design to turn agent capabilities into useful developer experiences.
- Improve reliability, performance, and operability across agentic systems.
- Coach engineers, raise the technical bar, and create clarity around priorities and tradeoffs.
WHAT WE’RE LOOKING FOR
- Experience managing and growing software engineering teams.
- Strong hands-on engineering experience with Go.
- Experience with React and TypeScript.
- Hands-on experience building systems around LLMs and agentic workflows.
- Experience with model APIs, tool calling, context management, or agent loops.
- Strong distributed systems knowledge.
- Working knowledge of AWS.
- Strong technical judgment and comfort working through ambiguity.
- A track record of helping engineers grow while maintaining a high execution bar.
OUR TECH STACK
- Backend: Go, Postgres
- Frontend: TypeScript, React
- Infrastructure: AWS, Kubernetes
- Observability: Prometheus, Grafana
- CI/CD: GitHub Actions
BONUS TACOS IF YOU HAVE
- (Tacos? If you need an ice-breaker, ask how we say thanks by giving tacos!)
- Experience building coding agents, developer tools, or cloud development environments.
- Experience with MCP, agent tools, or multi-agent systems.
- Experience with remote execution, sandboxing, or isolated compute.
- Experience building abstractions across multiple model providers.
- Deep experience with AWS, Kubernetes, Docker, or Linux.
- Open-source contributions or experience working directly with customers.
Coder’s agentic architecture is provider-agnostic. The foundation is built; this team is focused on making it more capable, reliable, and extensible as the space evolves.
ABOUT CODER
Coder is the leading platform for AI development Infrastructure, enabling enterprises to securely run human and AI-driven development workflows in consistent, governed environments. Coder provides self-hosted, agent-ready workspaces that unify developer productivity and platform governance. With Coder, enterprises can confidently evolve from human-only development to AI-assisted and autonomous workflows, without sacrificing security, compliance, or performance. Learn more at coder.com http://coder.com.
INTERVIEW PROCESS
We believe that the interview process should be transparent, consistent, and enjoyable. We value your time and hope to complete the interview process in two to four weeks, if schedules allow. Through your interviews, you will meet a mix of individual contributors, managers, and senior leaders.
AI USE DURING THE INTERVIEW PROCESS
As an AI company, Coder embraces the use of AI tools, and we want to be transparent about our expectations as you navigate our interview process.
Not permitted: Using AI assistance during conversational interviews.
Permitted: Using AI tooling for take-home assessments. Please flag where and to what extent it was used in your take-home. Your submission will not be penalized for using AI as long as it is done honestly.
OUR USE OF AI IN HIRING
We use AI tools to help manage our recruitment process efficiently and fairly. Specifically:
- Ashby and Brainerr help us review inbound applications by surfacing candidates who best match the role requirements we've defined. This tool does not make hiring decisions; it helps our team prioritize which applications to review first.
- Granola takes notes during our interview calls so our team can focus on the conversation with you.
All hiring decisions are made by humans. Our team reviews applications, conducts interviews, and makes final selections. AI tools assist us but never replace human judgment, and these practices are conducted in compliance with applicable data protection, AI governance, and labor laws. Your data is not used to train AI models.
In accordance with New York City Local Law 144, an independent bias audit has been conducted on "Automated Employment Decision Tools"; results are available for Ashby https://www.ashbyhq.com/downloadables/ashby-bias-audit-08-2024.pdf.
If you're applying for a role at Coder and have questions about how we use AI in our process, or if you'd like to request information about the data we collect, please contact careers@coder.com.
CODER IS A PROUD EQUAL OPPORTUNITY EMPLOYER
We are committed to providing equal employment opportunities to qualified applicants and do not discriminate on the basis of race, color, ancestry, religion, sex, pregnancy, gender, gender identity, gender expression, sexual orientation, national origin, age, marital status, genetic information, disability, protected veteran status or any other characteristic protected by federal, state, or local laws.
Location: São Paulo or Rio de Janeiro, Brazil
Why Join Exadel
We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.
From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.
What powers it all? Our people are ambitious, collaborative, and constantly evolving.
About the Client
A leading global digital banking platform and one of the largest neobanks in Latin America, headquartered in Brazil. The company provides a mobile-first suite of financial services—including credit cards, savings accounts, and investments—designed to eliminate bureaucracy and high fees. By leveraging advanced data analytics and a customer-centric digital infrastructure, the organization delivers transparent and accessible financial solutions to millions of users across Brazil, Mexico, and Colombia.
What You’ll Do
Design, build, test, and maintain AI agent capabilities, including tools, skills, commands, and prompts
Apply prompt-engineering techniques to improve agent accuracy, reliability, and usability
Define structured output contracts, error-handling mechanisms, and evaluation methods for measuring agent behavior
Develop extensions, plugins, and integrations for AI-powered development tools
Build and maintain reusable application templates that establish consistent engineering standards across generated projects
Develop developer-facing interfaces and internal tooling using React and TypeScript
Improve the developer experience through actionable feedback, clear error messages, reliable defaults, and streamlined workflows
Implement and maintain quality gates, including type checking, linting, automated testing, and build validation
Apply containerization and runtime standards to support secure and consistent application development
Collaborate with platform engineers to integrate AI capabilities with infrastructure, CI/CD pipelines, and deployment workflows
Monitor platform usage, identify friction points, and continuously improve the experience based on observed behavior and user feedback
Document technical decisions, agent behavior, platform capabilities, and development workflows
Incorporate AI agents into daily engineering activities and identify opportunities to improve their effectiveness
What You Bring
A solid foundation in application architecture, software engineering, and modern development practices
Hands-on experience designing and implementing AI agents, including tools, skills, commands, and prompt engineering
Experience evaluating AI agent behavior systematically using defined criteria, test cases, and supporting evidence
Experience with React and TypeScript, including modern frontend development patterns and build tooling
Experience building reusable application templates, developer tools, internal platforms, or self-service engineering capabilities
Knowledge of automated testing, type checking, linting, build validation, and software-quality practices
Familiarity with containerization and application runtime environments
Working knowledge of cloud infrastructure, CI/CD concepts, and application deployment workflows
Strong technical English skills, including written documentation and remote collaboration
Strong analytical and problem-solving abilities with excellent attention to detail
Ability to work independently, navigate ambiguity, and take ownership of technical outcomes
Interest in incorporating AI agents into everyday engineering workflows and continuously improving their performance
Nice to have
Experience developing plugins, extensions, or integrations for AI-powered development environments
Experience using Python for supporting services, automation, or AI-related workflows
Familiarity with enterprise application security, governance requirements, and engineering guardrails
Experience designing structured agent interfaces, typed outputs, and robust error-handling mechanisms
Understanding of cloud-native architectures, CI/CD pipelines, and production deployment practices
Experience improving developer productivity through internal platforms, reusable templates, or self-service tooling
Exposure to AI evaluation frameworks, observability, or agent performance monitoring
English level
Upper-Intermediate
Work Type:
Remote
Eligible Locations:
São Paulo or Rio de Janeiro, Brazil
Legal & Hiring Information
Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs
Compensation details are shared with candidates at the early stage of the recruitment process.
The offer is not binding until a signed contract is in place.
Your Benefits at Exadel
Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.
International projects
In-office, hybrid, or remote flexibility
Medical healthcare
Recognition program
Ongoing learning & reimbursement
Well-being program
Team events & local benefits
Sports compensation
Referral bonuses
Top-tier equipment provision
Exadel Culture
We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.
* Giving all our riders an excellent customer experience by the channels that we are available on. * Making sure that you are on top of our product/processes to provide the right information to all our riders.
Location: San Francisco; Seattle; New York City
ABOUT THE ROLE
The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes.
This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate.
KEY RESPONSIBILITIES
- Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state.
- Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes.
- Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability.
- Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls.
- Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost.
- Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety.
- Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes.
QUALIFICATIONS
- 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation.
- Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications.
- Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack.
- Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows.
- Deep expertise in at least one of the following:
- Evaluation infrastructure, benchmark design, and automated grading.
- Agent harnesses, tool interfaces, and reusable skills for complex workflows.
- Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows.
- Model selection, routing, and inference efficiency, including context management and caching.
- Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise.
- Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements.
- A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, and raising engineering quality through mentorship.
If you’re excited about this role, we encourage you to apply even if you don’t meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.
-Разрабатывать и поддерживать backend-сервисы на Python (FastAPI, asyncio). -Развивать логику диалогового агента: сценарии и состояния звонка, извлечение данных из реплик, работу с LLM.
Location: Almaty, Kazakhstan
Workplace: OnSite
Almaty, Kazakhstan · Trust & Safety Engineering
Why this role exists
An agent needs more than a model response to complete useful work. It needs tools, durable execution, permissions, context, and a way to recover when something fails. You'll build the backend that lets Higgsfield agents carry creative tasks from a user's request to a finished result. We're looking for an engineer we can trust with a problem: work out what is worth building, build it, and carry it through to users.
What you'll actually do
- Agent execution: build orchestration for multi-step tasks, tool calls, streaming updates, and cancellation.
- Durable workflows: implement checkpoints, resumability, retries, and recovery without duplicating actions.
- Tools and integrations: connect agents to generation, editing, and external services through clear, validated interfaces.
- Execution boundaries: enforce user permissions, tenant isolation, resource limits, and approval requirements for consequential actions.
- Evaluation and observability: trace failures, build regression cases, and improve task completion, latency, and cost.
- Ownership: understand a real user task → define success and build evaluation cases → scope the simplest useful workflow → ship → measure completion, reliability, and dollar impact → improve from failed runs. Our release cycle is days, not quarters, so your first shipped agent capability happens fast.
Must-haves
1. You've taken a difficult problem from an unclear starting point to a working system used in production, and can explain your own decisions, contribution, and results.
2. You can build reliable agent execution: state machines, concurrency, queues, recovery, model APIs, secure tool calls, and repeatable evaluations. You learn unfamiliar tools quickly and understand what you ship.
3. You choose the next steps, remove blockers, and ask for help when needed. You cut scope to test an idea, adapt from evidence, and keep working through difficult problems.
4. You investigate real user tasks and failed agent runs, use feedback to choose what to automate, and stop workflows that do not help users finish their work.
5. You take feedback, change your mind when the evidence changes, and do the work the team needs. You share knowledge and responsibility so others can operate and extend what you build.
Who this is not for
- You prefer deterministic application behavior without investigating model uncertainty.
- You prefer prototyping without owning evaluation, recovery, and production reliability.
Nice to have
- Production agents, workflow engines, or developer tools.
- High-throughput systems with heavy traffic, large data volumes, or many long-running jobs.
- Agent context management, memory, subagents, or parallel tool calls.
- Sandboxed execution and scoped authorization.
- Multimodal workflows involving images, video, or audio.
Interview process
1. Recruiter screen: role expectations, logistics, and fit.
2. Technical interview: a difficult system you shipped, what you personally decided and built, and how your work made the team more capable without leaving it dependent on you.
3. Additional technical interview, if needed: a deeper discussion of technical skills and open questions.
4. Product fit interview: scope a useful tool-using workflow, evaluate failures, and explain when user feedback would lead you to change or stop it.
5. Offer.
What we offer
Competitive base in USD, equity, relocation support, and ownership of systems that turn AI capabilities into completed creative work.
You will take an agent surface from operational research through specification, prototype, evaluation, and enterprise deployment, working hands-on throughout. Agent definition.
УдалённоUnited States; This position is required to be in the US Eastern Time Zone
middleSão Paulo or Rio de Janeiro, Brazil
San Francisco; Seattle; New York City
ОфисAlmaty, Kazakhstan; Competitive base in USD, equity, relocation support, and ownership of systems that turn AI capabilities into completed creative work
