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SeniorВ офисеПолная занятость

Senior Applied AI Engineer

Оценка ИИ

Отличная позиция в стабильной, но инновационной компании. Работа на острие технологий (Agentic AI) в уникальной нише EDA делает эту вакансию крайне привлекательной для профессионального роста.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубокой экспертизы в LLM-инженерии, включая создание агентных циклов и оптимизацию производительности. Высокая сложность обусловлена необходимостью внедрения AI в специфическую область проектирования электроники.

Анализ зарплаты

Медиана75 000 €
Рынок60 000 € – 95 000 €
Оценка ИИ

Зарплата для Senior AI ролей в Лиссабоне обычно выше среднего по рынку Португалии из-за дефицита кадров. Указанный диапазон соответствует топовым технологическим компаниям в регионе.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Applied AI Engineer position at Altium. With extensive experience in building production-ready LLM applications and a deep focus on agentic workflows, I am excited by Altium's vision of transforming hardware engineering through AI. My background in Python development and my hands-on experience with tool-calling, MCP servers, and evaluation pipelines align perfectly with the technical requirements of your R&D team.

In my previous roles, I have successfully moved AI projects from experimentation to production, focusing on cost and latency optimization through context compression and model cascading. I am particularly impressed by Altium's commitment to 'Agentic Hardware Engineering' and would welcome the opportunity to apply my skills in LangGraph and asynchronous services to enhance your Requirements Portal. I am a quick learner who thrives in multidisciplinary teams and is eager to contribute to the evolution of EDA tools.

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Составьте идеальное письмо к вакансии с ИИ-агентом

Составьте идеальное письмо к вакансии с ИИ-агентом

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Присоединяйтесь к Altium и создавайте будущее электроники с помощью передовых AI-агентов в Лиссабоне!

Описание вакансии

⚡️ Why Altium?

Altium is transforming the way electronics are designed and built. From startups to world’s technology giants, our digital platforms give more power to PCB designers, supply chain, and manufacturing, letting them collaborate as never before.

  • Constant innovation has created a transformative technology, unique in its space
  • More than 30,000 companies and 100,000 electronics engineers worldwide use Altium
  • We are growing, debt-free, and financially strong, with the resources to become #1 in the EDA industry

Why Altium Software Engineering?

Build the cloud platform that’s transforming electronics design. Altium Develop/Agile let design engineers communicate, collaborate and bring their ideas to market more efficiently than any platform in the industry. Altium offers the opportunity to conceive and build new product features for engineers who develop smart products.

The Requirements Portal delivers essential features on the Altium Develop/Agile platform for engineering teams to collaborate on their product requirements. It covers the entire lifecycle from importing with smart importers customer requirements, collaborating on them, connecting them to the electronics design, verifying them and creating relevant compliance documents.

  • Shape the future: You'll be part of a close-knit team with ambitious goals, but you'll also have the freedom and power to define the best way to achieve them. Collaborate with your team to map out the features and technical path that will bring our product vision to life;
  • Grow together, share knowledge: We foster a culture of continuous learning and knowledge sharing. You'll have the opportunity to learn from and mentor your teammates, contributing to a collaborative environment where everyone thrives;

If you like the idea of working in an environment that encourages creative and autonomous work, focuses on your growth potential and where there’s always room to discuss the quirks of living on this planet, then we might just be a perfect fit.

About the role

We’re looking for an experienced AI Engineer to join our team working at the frontier of applied AI in Requirements Management and Hardware Engineering more in general. 

This is a hands-on role where you’ll help build and evaluate real-world AI applications with immediate commercial impact. You’ll help design, develop, and deploy LLM-driven systems used by hardware product teams around the world, while learning how AI projects move from idea to production inside a product-led development team in the age of Agentic Hardware Engineering.

A day in the life of our AI Engineer

  • Develop agentic flows using off-the-shelf LLMs and applying modern harnessing methods (tool-calling, planning, skills, sub-agents, mcp servers, CLIs, etc.) to hardware design/requirement management use-cases.
  • Collaborate with software engineers, product managers, and designers in an agile, sprint-based environment to ship features and improvements
  • Build evaluation pipelines, design metrics and gather data to measure and improve the performance of AI-driven systems.
  • Extend test-suite, refining and running benchmarks on our AI systems.
  • Benchmark models, prompts and approaches for speed, cost and accuracy and improve results methodically using techniques with highest impact (meta prompting, fine tuning, RAG, caching, prompt compression, distillation, etc.)
  • Participating in the full AI product lifecycle: from early-stage experimentation to deployment and continuous improvement.

Who We’re Looking For

Essential skills:

  • Profound knowledge of LLM engineering and how LLM-based features are built and evaluated in production-ready environments
  • Advanced Python development skills to implement such systems
  • Production Experience with:
  • Agentic loops
  • Tool-calling
  • Agent orchestration
  • MCP servers
  • Evaluation and benchmarking pipelines.
  • Cost and latency optimization (context compression/model cascading etc)
  • Ability to plan experiments and execute tasks autonomously with an eye for detail
  • Quick learner to understand and keep up with the constantly evolving AI landscape
  • Experience in working in multi disciplinary teams to ship features to customers
  • Curiosity for user journeys and real-world use cases to validate solutions

Nice to have:

  • Production experience with:
  • + - Finetuning models

- Synthetic test data creation

- Distillation

- Agent Orchestration Debugging

+ Experience with (hardware) engineering software

+ Experience with developing end-to-end harnesses for agentic loops

+ Experience with building high concurrency asynchronous services

+ Experience with stateful agentic frameworks (like LangGraph)

🌍 Also, we would like you to know

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace.

💡 Learn more about why a career at Altium is an opportunity like no other:![](https://www.youtube.com/watch?v=cAYCOLpPLPE)https://www.youtube.com/watch?v=cAYCOLpPLPE

✈️ Altium Benefits: https://careers.altium.com/#s-benefits 

👏 Are you already an Altium employee?Please apply directly through our internal Greenhouse job board. If you have questions, please contact HR.

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Навыки

  • Python
  • LLM
  • Fine-tuning
  • Asynchronous Programming
  • RAG
  • LangGraph
  • Benchmarking
  • Model Distillation
  • Agentic Workflows
  • MCP servers

Возможные вопросы на собеседовании

Проверка практического опыта работы с современными протоколами взаимодействия AI-агентов.

Расскажите о вашем опыте внедрения MCP (Model Context Protocol) серверов в производственную среду. С какими основными трудностями вы столкнулись?

Оценка навыков оптимизации и понимания экономики AI-решений.

Какие стратегии вы используете для балансировки между стоимостью, задержкой (latency) и точностью при работе с LLM в высоконагруженных системах?

Проверка умения измерять качество работы AI, что критично для инженерного ПО.

Как вы проектируете пайплайны оценки (evaluation pipelines) для агентных систем, где результат не всегда детерминирован?

Оценка навыков работы с современными фреймворками для сложных AI-сценариев.

Опишите ваш опыт работы со stateful-фреймворками, такими как LangGraph. В каких случаях их использование оправдано по сравнению с простыми цепочками?

Проверка способности работать в междисциплинарной команде над сложным продуктом.

Как вы подходите к сбору требований от инженеров-электронщиков для создания инструментов автоматизации на базе AI?

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