AI engineer in agentic systems

Siemens; Lisboa; Hybrid; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Comprehensive health insurance

Mental health support

Active sports communities

Access to learning platforms

Mentoring and career development

Shuttle service

Job summary

Siemens ищет опытного инженера по искусственному интеллекту для проектирования и внедрения end-to-end AI-решений, включая RAG и LLM‑приложения. Вы будете работать в многонациональной команде и заботиться о чистоте кода, тестировании и CI/CD, применяя передовые MLOps практики.

Кандидат должен владеть Python, опытом работы с LLM-фреймворками и облачными технологиями, а также уметь донести сложные идеи до бизнес‑заказчиков и стейкхолдеров в Siemens Lisbon hybrid офисах.

Qualifications

• Требуется степень в области информатики/данных или эквивалентный опыт.
• 5+ лет опыта в разработке ПО, ML-инженерии или DS.
• Опыт развёртывания решений в продакшн, управление проектами с несколькими стейкхолдерами.
• Свободное владение английским языком.

Responsibilities

• Разрабатывать, внедрять и поддерживать end-to-end AI-решения (RAG, LLM-активируемые).
• Обеспечивать production‑grade практики: чистый код, тестирование, CI/CD, контейнеризация, мониторинг, MLOps/LLMOps.
• Работать в тесном международном коллективе и транслировать технические концепты non‑technical стейкхолдерам.

Skills

Python

LLMs

ML pipelines

English

Communication

Education

Степень в информатике/данных или смежной области

Tools

LangChain/LangGraph

PyTorch

Docker

Kubernetes

Job description

Описание:

At Siemens, we build technology solutions to shape the world we live in. We transform industries and societies by combining the real and digital worlds. With over 300.000 of the world’s most forward-thinking minds and the power of a presence in more than 190 countries, we make a truly global impact.

Задачи:

Design, develop, and deploy end-to-end AI solutions — RAG and retrieval pipelines, LLM-based applications, agentic workflows, and classical ML where it's the better tool — to improve Siemens processes and products. Bring production-grade practices to AI: clean code, testing, CI/CD, containerization, observability, and MLOps/LLMOps for evaluation, monitoring, and safe iteration. Lead initiatives from concept to deployment, translating business requirements into scalable technical solutions and ensuring timely delivery aligned with business objectives. Work in a lean, MVP-driven way — prototype fast, validate with real users, then harden what proves valuable. Work closely with an international team of diverse backgrounds — engineers, product managers, domain experts, and business stakeholders — to integrate AI solutions into existing systems and platforms. Clearly articulate complex technical concepts to non-technical stakeholders. Proactively raise concerns, suggest alternatives, and engage in constructive debate when appropriate. Mentor colleagues, share reusable patterns and reference architectures, and contribute to the overall skill development of the team.

Требования:

Degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, or a related field — or equivalent practical experience. A strong track record of shipped systems counts as much as a formal qualification. 5+ years in software engineering, machine learning engineering, or data science roles, including meaningful hands‑on experience with modern AI/LLM technologies. Proven ability to take solutions from exploration to production — not just prototypes and notebooks. Demonstrated ability to manage and deliver complex projects with multiple stakeholders. Strong programming skills in Python. Practical experience with LLM-based systems: prompt design, RAG architectures, vector search and embeddings, structured output, and evaluation. Experience with at least one agentic or LLM framework (e.g. LangChain/LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, OpenAI Agents SDK, Microsoft Agent Framework) and an understanding of what it takes to make agents reliable rather than merely impressive. Familiarity with ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn) and classical ML/NLP fundamentals. Experience with cloud-native development (Azure preferred; AWS or GCP equally welcome), including containerization (Docker/Kubernetes) and CI/CD. Experience designing and working with APIs, data stores, and integration layers (SQL and NoSQL; e.g. PostgreSQL, MongoDB, Azure AI Search, or comparable). Exposure to MLOps/LLMOps practices: versioning, deployment pipelines, tracing, evaluation, and monitoring of AI systems in production. Version control and collaborative engineering practices (GitHub/GitLab). Strong verbal and written communication: Ability to present ideas concisely and directly in international business contexts. Comfort proactively raising concerns, suggesting alternatives, and engaging in constructive debate. Experience bridging communication between global teams and navigating cultural differences in professional settings. Curiosity about the business domain, not just the technology — the best AI solutions come from engineers who understand the problem deeply. Independent working style with a proactive approach to problem-solving. High level of ownership and accountability for project outcomes. Excellent teamwork and collaboration abilities. Effective project management and organizational skills. Fluent English required. Будет плюсом: additional strength in TypeScript/Node.js, C#, Java, or Go is a plus, especially for building services and user-facing applications; big data and analytics platforms (Snowflake, Spark, Databricks), data visualization, enterprise platforms (Microsoft 365 / SharePoint, SAP, Salesforce), or a research background with publications; German or Portuguese is beneficial but not mandatory

Условия:

Work in diverse teams where every idea matters and innovation grows through collaboration and trust. Hybrid model, flexible hours, and a home office budget — because balance fuels performance.

• Comprehensive health insurance
• mental health support
• and active sports communities to keep you feeling your best.

• Access world‑class learning platforms
• mentoring
• and continuous development opportunities.

• Contribute to sustainability and volunteer initiatives
• enjoy partner discounts
• and take advantage of our convenient shuttle service.