DevOps & GenAI Engineer (f/m/div.)

Braga, Braga, pt

Company Description

The Bosch Group has more than 400 000 employees around the world, present in 60 countries, and we are proud to impact people’s lives and to work towards a more sustainable future.

Bosch Car Multimedia, S.A. belongs to the Automotive Electronics division and is focused on making the vehicles our third living space. About 3.600 associates are committed to develop and produce high quality technology that shape change in mobility worldwide. The company' success lies in its highly specialized and innovative team, and on the technological know-how which makes Bosch the leading supplier in the automotive market.

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference in mindsets, cultures, generations, identities and perspectives. Everyone should bring their authenticity and work together respectfully. Bosch is an employer that values diversity and equal opportunities. We welcome applications from people with disabilities and we can provide reasonable accommodations during the recruitment process and in the performance of professional activity. By including everyone and ensuring equal opportunities we unleash our full potential.

Job Description

As a DevOps & Generative AI Engineer, you will help develop innovative AI-powered solutions that support engineering teams throughout the product development lifecycle. By combining Generative AI, software engineering, and scalable platform technologies, you will contribute to transforming complex engineering processes into smarter, more efficient workflows.

Your contribution to something big:

Design and implement Generative AI agents that support engineering activities such as requirements analysis, documentation assistance, test interpretation, and failure analysis.
Develop AI solutions using Large Language Models (LLMs), embeddings, vector databases, and domain-specific knowledge sources.
Build and maintain Retrieval-Augmented Generation (RAG) pipelines for structured and semi-structured engineering data.
Integrate AI agents with engineering tools, databases, repositories, and enterprise platforms.
Ensure reliability, traceability, security, and responsible AI usage in regulated engineering environments.
Collaborate closely with engineering experts to evaluate solution performance, usability, and business value.
Document architectures, APIs, integration concepts, and operational guidelines.
Work together with security and compliance teams to implement trustworthy and compliant AI solutions.
Contribute to the continuous improvement of AI platforms, DevOps practices, and engineering processes.

Qualifications

What distinguishes you:

Education

Degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a comparable field.

Experience

Experience in Generative AI development, AI agent orchestration, AI-powered applications, or related areas.
Strong software engineering background with hands-on experience in Python and API-based architectures.
Experience working with microservices and modern software development practices.
Familiarity with structured and semi-structured data formats such as JSON, PDFs, and technical documentation.

Know-how

Good understanding of Large Language Models (LLMs), embeddings, vector databases, and RAG architectures.
Experience with AI agent frameworks such as LangChain, LlamaIndex, OpenAI Agents, CrewAI, Swarm, or MCP.
Knowledge of cloud-native development, DevOps practices, CI/CD pipelines, or platform engineering concepts is an advantage.
Experience with MLOps, AI observability, evaluation frameworks, or model deployment is a plus.
Familiarity with engineering workflows, PLM systems, or regulated industrial environments is beneficial.

Languages

Excellent English communication skills.
German language skills are considered an advantage.

Working Style and Methods

Structured, analytical, and solution-oriented way of working.
Ability to collaborate effectively in cross-functional and international teams.
Comfortable working in agile, iterative, and innovation-driven environments.
Strong focus on quality, reliability, and continuous improvement.

Personality

Curious and passionate about emerging technologies and AI innovations.
Proactive mindset with a strong sense of ownership.
Excellent communication and stakeholder management skills.
Open-minded team player who values diversity, inclusion, and different perspectives.