Senior Microsoft Azure AI Engineer

ZipRecruiter; Frankfurt; Hybrid; EUR 80.000 - 110.000; Vollzeit

Zusammenfassung

A leading company in the cloud data solutions space seeks a Senior Microsoft Azure AI Engineer to lead AI solution architecture. This role involves technical leadership, client engagement, and the establishment of best practices for MLOps. Ideal candidates should possess extensive experience in AI/ML solutions, strong system design skills, and proficiency in key Azure services. Join a collaborative team focused on innovation and impactful AI initiatives.

Qualifikationen

• 7+ years in data analytics and software development.
• Experience designing and implementing ML/AI solutions at scale.
• Relevant Azure and AI certifications are a plus.

Aufgaben

• Lead AI Solution Architecture for end-to-end AI/ML solutions.
• Engage with clients to identify AI opportunities.
• Establish MLOps best practices for scalable solutions.

Kenntnisse

German

English

Azure ML

Databricks

Data Lake/Synapse

Cognitive Services

Azure OpenAI

Python

TensorFlow

PyTorch

Ausbildung

Bachelor's or Master's in Computer Science

Jobbeschreibung

Job Description

As a Senior Microsoft Azure AI Engineer (m/w/d) Lead AI Solution Architecture, you're responsible for the end-to-end architecture of AI/ML solutions on Azure. You provide technical leadership to teams in implementing best practices and MLOps, and work closely with clients to translate their business needs into innovative AI solutions.

Activities

1. Lead AI Solution Architecture: Own the end-to-end architecture for AI/ML solutions on Azure, from concept and design to deployment. Develop high-level solution designs that integrate with clients' existing data platforms and infrastructure.
2. Client Engagement: Work closely with enterprise clients to understand business challenges and identify opportunities where AI/ML can drive value (e.g., predictive maintenance, drug discovery, risk modeling). Translate these needs into solution roadmaps and technical plans.
3. Technical Leadership: Provide hands-on technical leadership to delivery teams. Guide Azure AI Engineers and Data Engineers in implementing best practices for data preparation, model development, and cloud deployment. Mentor team members and review designs/code to ensure quality.
4. MLOps & Best Practices: Establish and enforce MLOps best practices, including reproducible workflows, CI/CD for ML models, automated testing, and monitoring. Ensure solutions are scalable and maintainable.
5. Innovation & Generative AI: Stay updated on AI trends and Azure services. Evaluate new technologies like Azure Cognitive Services, Azure OpenAI, open-source LLM frameworks, and RAG, incorporating generative AI capabilities to enhance client solutions.
6. Cross-Project Impact: Oversee multiple AI projects, ensuring architectural consistency and reuse of best practices across engagements.
7. Internal Capability Building: Contribute to internal AI capabilities by developing architecture blueprints, accelerators, and reference implementations. Lead knowledge-sharing sessions and training to upskill colleagues.

Requirements

• Proven Experience: 7+ years in data analytics and software development, with 4-5 years designing and implementing ML/AI solutions at scale. Experience delivering enterprise AI projects.
• Skills: Fluent in German and English. Deep knowledge of Azure data and AI services (Azure ML, Databricks, Data Lake/Synapse, Cognitive Services, Azure OpenAI). Ability to architect solutions integrating these services.
• Architectural Skills: Strong system design and integration skills. Experience defining solution architectures covering data ingestion, feature engineering, model deployment, and monitoring. Familiarity with microservices and cloud data pipelines is a plus.
• MLOps & Software Engineering: Solid understanding of MLOps principles, experience with ML lifecycle management, proficiency in Python, TensorFlow/PyTorch, and DevOps processes.
• Leadership & Communication: Excellent leadership and interpersonal skills. Ability to communicate complex AI concepts to stakeholders and lead technical teams.
• AI Knowledge: Broad knowledge of ML and AI techniques, deep learning, NLP, and familiarity with Generative AI and LLMs. Understanding of Azure AI Foundry concepts.
• Certifications: Relevant Azure and AI certifications are a plus, such as Microsoft Certified: Azure Solutions Architect Expert, Azure AI Engineer Associate, or Databricks Certified Generative AI Engineer.
• Education: Bachelor's or Master's in Computer Science, Data Science, or related field, or equivalent professional experience.

Team: You will be part of a collaborative, remote-friendly team that values continuous learning and impactful cloud-data solutions.

Application Process: After applying, you'll have an initial session with a recruiter, followed by a technical discussion with our experts. If aligned, an offer will be extended within 48 hours.