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Lead Solutions Architect - Generative AI (EMEA Emerging DNB)

Databricks· Engineering
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Hybrid (United Kingdom)full-timePosted 3w ago

About the role

Lead technical authority on Generative AI for the EMEA Emerging Digital Natives and Startups business unit. This is a highly technical, customer-facing individual contributor role focused on shaping GenAI architectures, proofs-of-concept, and MT/roadmap influence across high-growth accounts.

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 domains where quality and safety are paramount.
  • 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 our ~70-person SA/SE organisation.
  • Represent Databricks externally as a technical thought leader — conference talks (e.g., Data + AI Summit), blogs, and customer executive briefings.

Qualifications

  • Strong understanding of the LLM landscape, including leading proprietary and open-source models and providers, with the ability to differentiate their capabilities, trade-offs, and suitability for different use cases, and to articulate a clear, informed point of view (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.
  • Strong 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 comfort building production-quality reference implementations.
  • Experience with the Databricks platform — or the ability to ramp on it quickly — including Mosaic AI, Model Serving, Vector Search, and Unity Catalog. Cloud experience across AWS, Azure, or GCP.
  • Excellent communication and consultative skills: able to earn the trust of both hands-on engineers and senior technical executives, and to explain complex GenAI trade-offs clearly.
  • A track record of technical leadership and mentorship — someone who elevates the people around them.
  • Comfort operating at the pace of digital-native and high-growth customers, where speed, iteration, and technical credibility win the deal.
  • Based in the United Kingdom and able to work across EMEA time zones, with willingness to travel to customer sites within the region as needed.
  • Background helping digital-native customers build data and ML solutions (e.g., prior experience at a data/ML platform or consulting vendor) is a strong plus.

Skills

Required:GenAI / LLM landscape understandingLLM application patternsMLOps lifecyclePython / ML ecosystemDatabricks platformCommunication and stakeholder management

Benefits

  • For specific details on the benefits offered in your region click here (link provided in the posting).
Last updated Oct 1, 2026. Interested? Apply on the company site.

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