Systems Engineer - Zentrales Server Eventmanagement (m/w/d)

Who We Are
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

You Will

• Own the design, analysis, and verification & validation of assigned subsystems within our autonomous vehicle system architecture.
• Collaborate with cross-functional teams to develop and deploy autonomous driving systems.
• Define and track KPIs for your areas to support data-driven engineering and system performance.
• Build data collection and analysis pipelines that support verification & validation processes.
• Author and maintain requirements documentation, traceability, and system architecture artifacts.
• Define system behaviors for critical safety scenarios and contribute to robust, well-reasoned designs.
• Surface risks early and help coordinate solutions and mitigations with the teams involved.
• Mentor junior engineers and contribute to team engineering practices.
• Be open to travel up to 25%.

You Have

• Bachelor's degree in Computer Science, Engineering, Mechatronics, Aerospace, or a related field (or equivalent experience).
• 4+ years of experience working on autonomous systems or safety-critical systems.
• Hands-on experience with systems engineering (e.g., V Model, requirements documentation, traceability, verification & validation).
• Basic proficiency in Python and SQL.
• Experience contributing to interdisciplinary teams developing and deploying robotic systems or autonomous vehicles with safety-critical components.
• Exposure to functional safety and SOTIF concepts.
• Strong ability to communicate technical issues and solutions clearly to both engineering and non-engineering audiences.
• Hands-on approach with a willingness to engage deeply and enjoy the work.

We Prefer

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field.
• Experience with requirements management tools such as DOORS, Jama, Flow, Polarion, or Enterprise Architect.
• Working knowledge of safety standards such as ISO 26262, ISO 21448, UL 4600, IEC 61508, or ISO 3691.

Wir gehören zu den Top-Adressen in der IT-Welt und fokussieren uns auf die Optimierung der Kerngeschäfts­prozesse unserer Kunden. Durch den smarten Einsatz maßgeschneiderter IT-Lösungen unterstützen wir unsere Kunden dabei, das Beste aus ihrem Business und aktuellen Technologien herauszuholen. Unseren Erfolg aber erreichen wir nur durch eins: die Menschen bei adesso! Sie bringen Ideen, fachliches Know how und Technologien zusammen. Gemeinsam programmieren wir (deine) Zukunft bei adesso.

DEINE ROLLE

• Data-Pipelines umsetzen: Du konzipierst und implementierst robuste Data-Pipelines, Data Ingest und Data-Processing auf Basis von Open-Source-Komponenten wie Apache Airflow, Kafka, Spark oder Trino und sorgst dafür, dass Daten zuverlässig, performant und nachvollziehbar fließen.
• Analytics-Plattformen entwickeln: Du entwickelst containerbasierte Analytics-Plattformen und entwirfst effiziente CI/CD-Pipelines auf Basis von Kubernetes, sodass neue Features und Änderungen sicher und automatisiert in Produktion gelangen.
• Plattformen bereitstellen & automatisieren: Du verantwortest das automatisierte Deployment der Analytics-Plattformen – z. B. mit Helm-Charts und Tools wie ArgoCD – und stellst sicher, dass Deployments reproduzierbar und stabil sind.
• Plattformen betreiben & absichern: Du integrierst Datenplattformen in bestehende Kundenlandschaften, inklusive IAM, Monitoring und Logging, und trägst so aktiv zu Stabilität, Sicherheit und Transparenz der Lösungen bei.
• Business-Anforderungen in Data-Products übersetzen: Gemeinsam mit unseren Kunden verstehst du fachliche Anforderungen und setzt sie mit Open-Source-Analytics-Services auf Kubernetes-Basis um – mit dem Ziel, unsere Kunden auf ihrem Weg zur Datensouveränität ganzheitlich zu begleiten.
• Lernen & Wissen teilen: Du hältst dein Wissen im Cloud-, Data- und Software-Engineering-Umfeld kontinuierlich aktuell, probierst neue Technologien aus und gibst deine Erfahrungen im Team und beim Kunden weiter – z. B. in Projekten, Communities oder internen Formaten.

DEIN PROFIL

• Ausbildung & Erfahrung: Du bringst ein abgeschlossenes Studium (oder eine vergleichbare Qualifikation) mit und hast bereits praktisch mit Komponenten wie Spark, Kafka, Airflow o. Ä. gearbeitet – idealerweise in produktionsnahen Projekten.
• Kubernetes Know-How: Du hast praktische Erfahrung im Umgang mit Kubernetes (z. B. Deployment-/Service-Definitionen, Umgang mit Secrets, Helm-Charts) und hast Spaß daran, containerisierte Anwendungen und Plattformen zu bauen.
• Kenntnisse in der Softwareentwicklung: Du verfügst über solide Programmierkenntnisse in Java, Scala oder Python und hast bereits mit Build- und CI/CD-Tools wie Maven, sbt, Gradle, Git oder ähnlichen Werkzeugen gearbeitet.
• Verständnis für Cloud- und Infrastrukturkonzepte: Begriffe wie IaaS, PaaS und SaaS kannst du einordnen, und du hast erste Erfahrungen mit Infrastructure-as-Code-Ansätzen (z. B. Terraform, Ansible oder Puppet), um Infrastruktur reproduzierbar und versionierbar aufzubauen.
• Leidenschaft für Daten & moderne Plattformen: Du hast Freude daran, komplexe Datenlandschaften zu verstehen, neue Technologien im Data- und Analytics-Umfeld auszuprobieren und Lösungen end-to-end mitzugestalten.
• KI Kompetenz: Du setzt KI-Tools in deinem Fachgebiet souverän ein, bewertest die Ergebnisse kritisch und unterstützt Kunden und adessi dabei, Potenziale von KI zu nutzen.
• Sprachkenntnisse: Deine sehr guten Deutsch- und guten Englischkenntnisse ermöglichen dir eine sichere Kommunikation.

Unser Versprechen: Du wirst dich bei uns wohlfühlen! Kollegial, familiär und auf Augenhöhe – wir leben Austausch, Teamgeist und einen respektvollen Umgang miteinander. Diversität und verschiedene Blickwinkel werden bei uns genauso geschätzt wie du als Mensch. Das und viel mehr steht für unser ganz besonderes Wir-Gefühl. Für das es sogar ein Wort gibt: adessi.

Unsere Kultur und das Zusammenarbeiten sind geprägt von gegenseitiger Wertschätzung, Anerkennung und Unterstützung. Das verbindet uns hierarchieübergreifend – auch im Home-Office. So belegen wir zum wiederholten Mal den 1. Platz beim Wettbewerb „Deutschlands Beste Arbeitgeber in der ITK“!. Unser umfangreiches Trainingsangebot und ein transparentes Laufbahnstufenmodell für alle sorgen dafür, dass deine Entwicklung bei uns nicht stillsteht. Denn gemeinsam zu wachsen und Chancengeber zu sein, das ist programmiert in unserer DNA.

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As Part Of Our Team, You Will

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

We’ll be happy to have you on our team if you have:

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our Ideal Candidate Would Have Experience With

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with:

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

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.

We are looking for an
Engineering Manager
to join the
OREO (Observability Reliability Engineering Obsession)
team in
Platform Engineering
.As an
Engineering Manager
, your mission will be to lead the Reliability & Observability team and drive the evolution of Doctolib's observability platform, supporting the exponential growth of Doctolib services while building and empowering a world-class SRE team.Working in the tech team at Doctolib involves building innovative products and features to improve the daily lives of care teams and patients. We work in feature teams in an agile environment, while collaborating with product, design, and business teams.You will lead a team of Site Reliability Engineers who are responsible for shaping Doctolib's observability strategy and ensuring our platform remains reliable, debuggable, and scalable. This role sits at the intersection of people management, technical leadership, and strategic planning with a particular focus on building organizational capabilities around logging, metrics, tracing, and alerting.Your team also owns and operates critical transversal services that enable secure, scalable infrastructure management across the organization, including HashiCorp Vault for secrets management and Terraform Enterprise for infrastructure as code.Your responsibilities include but are not limited to: 
People Leadership:

• Lead, coach, and grow a team of Site Reliability Engineers, supporting their technical development and career progression
• Create a culture of operational excellence, continuous improvement, and psychological safety within the team
• Conduct regular 1:1s, performance reviews, and career development conversations
• Recruit, onboard, and retain top SRE talent aligned with Doctolib's mission and values

Technical Strategy:

• Partner with SREs and senior engineers to define and evolve the observability strategy across the platform, focusing on logging, metrics, tracing, and alerting
• Own the strategy and evolution of critical transversal services including HashiCorp Vault and Terraform Enterprise
• Drive prioritization and roadmap planning for large-scale reliability and observability initiatives
• Ensure alignment between team objectives and broader engineering and business goals
• Advocate for and allocate resources toward reducing technical debt and improving developer experience

Operational Excellence:

• Own the team's on-call experience and contribute to the incident response processes, ensuring sustainable practices and continuous improvement
• Ensure high availability and reliability of transversal services that are critical to the entire engineering organization
• Lead postmortem reviews and drive systemic improvements to prevent recurring issues

Cross-functional Collaboration:

• Work closely with Product Managers, Engineering Managers, and architects to align observability capabilities with product and platform needs
• Partner with security and infrastructure teams to evolve secrets management and IaC practices across the organization
• Represent the OREO team in engineering leadership forums, architectural reviews, and strategic planning sessions
• Foster strong partnerships with software engineering teams to improve instrumentation quality and adoption of observability best practices

About our tech environment

• Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components.
• Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
• We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here and learn about our first AI hackathon here!

Who you are
Before you read on — if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.

• You have at least 5+ years of software engineering or SRE experience, with a strong technical background in cloud-native environments (preferably AWS, GCP, and/or Kubernetes-based)
• You have 3+ years of engineering management experience, leading technical teams (ideally SRE, platform, or infrastructure teams)
• You have deep understanding of observability tooling and architecture (Fluent Bit, OpenTelemetry, Loki, Elasticsearch, Prometheus, Thanos, Datadog)
• You have experience with infrastructure as code (Terraform, OpenTofu) and secrets management systems (Vault, AWS Secrets Manager)
• You have proven ability to balance technical depth with people leadership, able to mentor engineers, review technical designs, and guide architectural decisions

Now it would be fantastic if you:

• Have experience scaling SRE or platform teams in fast-growing, high-traffic environments
• Have background in designing and operating high-scale telemetry pipelines
• Have hands-on experience with HashiCorp Vault and Terraform Enterprise in production environments
• Have hands-on experience with backend programming languages (e.g., Go, Python, Ruby)
• Have experience driving cultural and technical transformations

What we offer

• Free comprehensive health insurance for you and your children
• ParentCare Program: Enjoy full salary coverage (100%) during your first month of birth leave, and 75% during the second, covered by Doctolib
• Free mental health and coaching services through our partner Moka.care
• For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
• Work from EU countries and the UK for up to 10 days per year, thanks to our flexibility days policy
• Work Council subsidy to refund part of sport club membership or creative class
• Up to 14 days of RTT
• A subsidy from the work council to refund part of the membership to a sport club or a creative class
• Lunch voucher with Swile card

The interview process

• 30-min phone screen with a Tech Recruiter
• 1h30 technical interview (SRE System Design & Architecture)
• 1h15 behavioral interview (Leadership & People Management)
• 1h30 Engineering Management case study (team scenarios, prioritization, and conflict resolution)
• 1h manager interview with Senior Engineering Leadership
• At least one reference check

Job details

• Permanent position
• Full-time
• Berlin
• Start date: as soon as possible

If you would like to find out more about tech life at Doctolib, feel free to read our latest Medium blog articles!
At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of discrimination.
The more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, disability.
To ensure equal opportunities, we invite you to exclude personal information (e.g. pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.
Join us in building the healthcare we all dream of!
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