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Senior Solutions Architect - AI & ML Engineer

DatabricksStockholm, Sweden
On-site Full-time

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Experience Level

Senior

Qualifications

What We Look For:7+ years of hands-on industry ML experience in at least one of the following areas:ML Engineer: Experience in building and maintaining production-grade cloud infrastructure (AWS/Azure/GCP) for ML applications, including drift monitoring. AI Engineer: Proficiency in the latest techniques involving LLMs and agentic systems, including vector databases, fine-tuning LLMs, and deploying LLMs using tools like HuggingFace and Langchain. Familiarity with data engineering concepts. Strong communication skills and the ability to work collaboratively in cross-functional teams. Passion for technology and a commitment to continuous learning and improvement.

About the job

Job ID: FEQ327R156

Role Overview

Databricks is seeking a Senior Solutions Architect with deep expertise in AI and ML Engineering to join the team in Stockholm, Sweden. This specialist role serves as a key technical resource for both Databricks clients and internal Field Engineering, focusing on helping enterprise and strategic customers design scalable, production-ready machine learning and AI applications on the Databricks platform. The position involves close collaboration with Solution Architects and offers the chance to work hands-on with technologies in Generative AI, MLOps, and broader machine learning fields. There are also opportunities to mentor others and contribute to AI thought leadership within the company.

What You Will Do

  • Design and implement production-grade ML and AI solutions for clients using the Databricks platform, including agents, end-to-end ML pipelines, training and inference optimization, and integration with cloud-native services.
  • Serve as a trusted advisor for enterprise Generative AI projects, including Retrieval-Augmented Generation (RAG) architectures, agentic systems, and natural language querying of structured data.
  • Develop, scale, and optimize customer AI workloads, applying strong MLOps practices to support deployment across different domains.
  • Provide advanced technical support to Solution Architects throughout the sales cycle, covering areas such as feature engineering and model monitoring, and engage with the broader ML expert community at Databricks.
  • Collaborate with product and engineering teams to represent customer needs, help set priorities, and influence the product roadmap to support the adoption of Databricks' AI solutions.

About Databricks

Databricks is a leader in the cloud data and AI space, providing a unified platform to simplify data engineering and analytics. By integrating machine learning and data science workflows, Databricks enables organizations to innovate faster and achieve their business goals more effectively.

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