Senior Solutions Architect (DS/ML/GenAI/LLM)
Role details
Job location
Tech stack
Job description
- Develop customer engagement strategies in partnership with Account Executive(s) in your designated territory.
- Coach junior Solutions Architects and teams on use case prioritisation and building technical champions.
- You will influence stakeholders at all levels through complex engagements with the broader cloud ecosystem and third-party applications, ensuring they are excited by the Databricks vision and solution strategy.
- Be a 'champion' for both customers and colleagues, operating as an expert solution architect and trusted advisor for significant data analytics architecture, design, and adoption of the Databricks Lakehouse platform.
- Contribute to Databricks' technical community engagement by developing customer-facing collateral and leading workshops, seminars, and meet-ups.
- Opportunity to continue your development in one of four tracks - technical specialisation, industry vertical thought leadership, strategic customer vision, and people management. What we look for
Requirements
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Hands-on experience in technical pre-sales or consultancy, with a strong background in Data Science - traditional Machine Learning, Deep Learning, Artificial Intelligence or Generative AI.
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Demonstrated ability to architect end-to-end Data & AI solutions, with specific expertise in modern Generative AI concepts (e.g., fine-tuning, RAG, MLOps for LLMs), using either open source and/or ISV tools such as Dataiku, Domino, DataRobot etc.
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Strong proficiency in a core programming language (e.g., Python, SQL) and a willingness to learn (or existing knowledge of) Spark.
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Proficiency with big data analytics technologies and public cloud platforms (AWS, Azure, or GCP).
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Hands-on expertise in designing and delivering complex proofs-of-concept (PoCs). Pre-Sales & Customer-Facing Skills:
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Proven ability to engage with customers in a technical sales capacity: challenging assumptions, guiding discussions to clear outcomes, and communicating both technical and business value propositions.
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Experience in the full pre-sales lifecycle, including use case discovery, solution scoping, and delivering complex solution architecture designs to diverse audiences (from engineers to executives).
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A customer-centric mindset with a passion for building client relationships and internal partnerships with account teams. Seniority & Leadership:
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Demonstrated experience in coaching and mentoring junior team members to help them develop their technical and customer-facing skills. Logistics:
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Ability to commute to the London office regularly.
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Willingness and ability to travel approximately 20-30% of the time across UK&I and EMEA for customer visits.
