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Lead Solutions Architect - Generative AI (EMEA Emerging DNB)

Databricks· Engineering
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Hybrid (Sweden)full-timePosted 5d ago

About the role

Lead technical authority on Generative AI for the EMEA Emerging Digital Natives and Startups business unit. Owns GenAI strategy and delivery from concept to production across high-growth accounts, with mentorship of the regional field team and external thought leadership.

Responsibilities

  • Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting the most strategic and complex customer engagements across our digital-native and born-in-the-cloud accounts.
  • Partner with EMEA Emerging DNB Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation.
  • Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance).
  • Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches for domain-specific quality and safety.
  • Act as a bridge to Product and Engineering — channel field and customer feedback into the roadmap and represent the roadmap back to the field.
  • Enable and mentor the broader EMEA Emerging DNB Field Engineering team through workshops, reference architectures, and internal enablement, multiplying GenAI expertise across the ~70-person SA/SE organisation.
  • Represent Databricks externally as a technical thought leader — conference talks, blogs, and customer executive briefings.

Qualifications

  • Strong understanding of the LLM landscape including proprietary and open-source models and providers, with the ability to differentiate capabilities and articulate a POV to customers.
  • Deep expertise in the modern GenAI stack: LLM application patterns (RAG, agents, tool use), fine-tuning and model customization, prompt and evaluation engineering, and LLM guardrails/safety.
  • Foundations in machine learning and deep learning, including distributed training, GPU workloads, and the full MLOps lifecycle (tracking, registry, serving, monitoring).
  • Proficiency in Python and the ML ecosystem (PyTorch/Transformers, MLflow, Spark), and experience building production-quality reference implementations.
  • Experience with the Databricks platform — or the ability to ramp quickly — including Mosaic AI, Model Serving, Vector Search, and Unity Catalog. Cloud experience across AWS, Azure, or GCP.
  • Excellent communication and consultative skills; ability to earn trust of engineers and senior technical executives and explain GenAI trade-offs clearly.
  • Track record of technical leadership and mentorship; ability to elevate others.
  • Comfort operating at high-growth, fast-paced customer environments; speed and credibility matter.
  • Based in the United Kingdom and able to work across EMEA time zones; willingness to travel within the region.

Skills

Required:GenAI / LLM landscape expertiseGenAI stack masteryMLOps and ML lifecyclePython / ML ecosystemDatabricks platform experienceCommunication / stakeholder managementLeadership / mentorship

Benefits

  • Benefits details available via regional link in job description.
Last updated Oct 22, 2026. Interested? Apply on the company site.

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