Lead Solutions Architect - Generative AI (EMEA Emerging DNB)

The shape of it

In the posting’s own words

We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business unit — one of the fastest-moving, most technically ambitious patches in EMEA. Our customers are digital-native and cloud-native companies who build on the frontier: they adopt GenAI early, scale fast, and expect their technical partners to be as sharp as their own engineers.

What it asks for · 5

• 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.
• 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.
• A track record of technical leadership and mentorship — someone who elevates the people around them.

Also a plus

• Public technical presence: conference speaking, published talks, blogs, or open-source contributions in the ML/GenAI space.
• Domain depth in a regulated or high-stakes industry (healthcare/life sciences, financial services) where model quality, evaluation, and safety are critical.
• Experience partnering with Product and Engineering teams to influence roadmap.

What the job covers

• 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 our 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), tuned to the fast iteration cycles Emerging DNB customers expect.
• 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.

Tools and skills named

Words the posting leans on

• customers12×
• genai9×
• technical8×
• llm7×
• emea emerging6×
• emerging dnb6×
• model6×
• field5×
• account4×
• build4×
• deep4×
• digital-native4×
• engineering4×
• evaluation4×
• experience4×
• learning4×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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