Role Description Du bist die technische Schlüsselfigur in Enterprise-Projekten auf AWS. Du sitzt mit Kunden zusammen, verstehst ihre Herausforderungen und entwirfst Lösungen. Dann orchestrierst du AI Agents, lässt Infrastructure as Code generieren, prüfst den Output kritisch und iterierst. Nicht Zeile für Zeile. Sondern Architektur für Architektur. - Du entwirfst hochverfügbare AWS-Architekturen und setzt sie mit AI-gestütztem IaC um - Du arbeitest direkt mit Kunden an Cloud-Strategien und Migrationsprojekten - Du nutzt AI CLI-Tools als Multiplikator: Claude Code, Cursor oder Gemini CLI - Du mentorst andere Engineers und definierst technische Standards - Du triffst Architekturentscheidungen und übernimmst Verantwortung für das Ergebnis Qualifications - Mindestens 5 Jahre Erfahrung mit AWS und Cloud-Architekturen - AWS Professional Zertifizierung oder vergleichbar - Erfahrung mit mindestens einem AI CLI-Tool (Claude Code, Cursor, Gemini CLI) - Solide Kenntnisse in IaC (Terraform, CDK oder CloudFormation) - Sicherheitsbewusstsein für Enterprise-Anforderungen - Du kannst komplexe technische Zusammenhänge verständlich kommunizieren - Fließend Deutsch und Englisch Benefits - Flexible Arbeitszeiten und 100% Remotearbeit - Zugang zu AI-Tools und LLM-Keys. Nicht als Benefit, sondern als Arbeitsmittel - Echte Enterprise-Projekte mit Ownership. Du baust Produkte, auf die du stolz sein kannst - AWS-Zertifizierungen und Konferenzen - Ein Team von ~30 Engineers, das Wissen teilt statt hortet - Keine Folien-Kultur. Wir arbeiten an der Sache, nicht am Konzept Company Description FNTIO sind AI-First Systems Engineers für Enterprise. Wir verbinden tiefe Cloud- und AI-Expertise mit Hands-on-Mentalität, um Produkte zu bauen, die Unternehmen wirklich transformieren. Keine Buzzwords, kein Body Leasing. Ergebnisse.

• Design, Build, and Maintain Scalable ML Infrastructure: Lead the design and development of scalable machine learning infrastructure on AWS, utilizing services like AWS Sagemaker for efficient model training and deployment. • Collaborate with Product Teams: Work closely with product teams to develop MVPs for AI-driven features, ensuring quick iterations and market testing to refine solutions effectively. • Develop Monitoring & Alerting Frameworks: Create and enhance monitoring and alerting systems for machine learning models to ensure high performance, reliability, and minimal downtime. • Support Marketing Team’s AI Utilization with an eye on Cross-Departmental impact: Enable various departments within the organization to leverage AI/ML models, including cutting-edge Generative AI solutions, for different use cases. • Provide Production Support: Offer expertise in debugging and resolving issues related to machine learning models in production, participating in on-call rotations for operational troubleshooting and incident resolution. • Scale ML Architecture: Design and scale machine learning architecture to support rapid user growth, leveraging deep knowledge of AWS and ML best practices to ensure robustness and efficiency. • Mentor and Elevate Team Skills: Conduct code reviews, mentor team members, and elevate overall team capabilities through knowledge sharing and collaboration. • Stay Ahead of the Curve: Stay updated with the latest advancements in machine learning technologies and AWS services, driving the adoption of cutting-edge solutions to maintain a competitive edge.

• Evangelise the enablement of AI across the organisation. • Collaborate closely with the CSO, Data Science and other teams. • Develop, train, evaluate, and optimise ML and deep learning models. • Build and validate generative AI solutions. • Implement data pipelines, feature engineering, and model evaluation workflows. • Deploy, monitor, and maintain ML models in production. • Ensure all AI/ML solutions meet quality, explainability, compliance, and performance requirements. • Provide thought leadership on AI/ML strategy, governance, and delivery best practices. • Ensure alignment with security, ethical AI, privacy, and regulatory requirements. • Create and maintain documentation on AI and Machine Learning processes and systems.

Role Description The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote. The impact you will have: - Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems. - Own production rollouts of consumer and internally facing GenAI applications. - Serve as a trusted technical advisor to customers across a variety of domains. - Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally. - Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap. Qualifications - Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy. - Expertise in deploying production-grade GenAI applications, including evaluation and optimizations. - Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.). - Experience building production-grade machine learning deployments on AWS, Azure, or GCP. - Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience. - Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike. - Passion for collaboration, life-long learning, and driving business value through AI. - [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets. Requirements - Pay Range Transparency: Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. - Local Pay Range: $152,900 — $210,155 USD Benefits - At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.