Role at a glance
- Salary
- Not Disclosed
- Location
- United Kingdom - London
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 10+ years of hands-on industry DS/ML experience
- Education
- Master's
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Senior Specialist Solutions Architect serves as a technical expert for Databricks customers and the Field Engineering organization, partnering with Solution Architects on production-grade ML and AI applications on the Databricks Data Intelligence Platform. The role focuses on enterprise GenAI, ML, MLOps, and LLMOps solutions while influencing product direction and supporting AI platform adoption.
What You'll Do
- Design and implement production-level ML and AI workloads, including end-to-end pipelines, training and inference optimization, MLOps...
- Develop enterprise GenAI solutions involving RAG architectures, agentic systems, AI observability, and natural language querying of...
- Build MVPs, lead technical deep-dive sessions, and provide advanced technical support to Solution Architects during technical sales cycles.
- Collaborate with product and engineering teams to represent customer needs, define priorities, and influence the platform’s AI roadmap.
- Create technical tutorials and training materials, present at industry conferences, and lead hackathons.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Hands-on experience building production-grade ML and AI workloads, cloud infrastructure on AWS/Azure/GCP, distributed Spark-based systems, data engineering concepts, LLMs, agentic systems, vector databases, fine-tuning, deployment tools such as HuggingFace and Langchain, and communicating complex technical concepts to technical and non-technical audiences.
Required
- 10+ years of hands-on industry DS/ML experience
- Hands-on experience working with Distributed Spark based systems
- Experience with data engineering concepts or a good understanding of data engineering concepts
- Graduate degree in a quantitative discipline or equivalent practical experience
- Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences
Preferred
- Minimum of 5+ years of customer-facing experience
- Experience working with Apache Spark™ to process large-scale distributed datasets
Original job description
Content provided by the employer
Original job description
Content provided by the employer
ReqID: FEQ427R340
Location: London
Skills: Platform & Security
Mission
As a Senior Specialist Solutions Architect, you will serve as the trusted technical expert for Databricks customers and the Field Engineering organization. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform. You will also continue to sharpen your technical expertise in cutting-edge areas like GenAI, ML, MLOps, and LLMOps, while mentoring colleagues and establishing yourself as an AI thought leader.
Impact you will have
- Architecting Workloads: Design and implement production-level ML and AI workloads, including end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services.
- GenAI Leadership: Serve as a practitioner for enterprise GenAI solutions, specializing in RAG architectures, agentic systems (including tool-calling, multi-agent orchestration, and guardrails), AI observability, and natural language querying of structured data.
- Provide advanced technical support to Solution Architects during the technical sales cycle by building MVPs, leading deep-dive sessions, and aligning AI solutions with complex customer business challenges.
- Product Influence: Collaborate cross-functionally with product and engineering teams to represent the voice of the customer, define priorities, and influence the platform’s AI roadmap.
- Thought Leadership: Drive community growth and AI platform adoption through the creation of technical tutorials and training materials, as well as by presenting at industry conferences and leading hackathons.
What we look for
- Experience: 10+ years of hands-on industry DS/ML experience, with a focus on either:
- ML Engineering: Building/maintaining production-grade cloud infrastructure (AWS/Azure/GCP) that supports deployment of ML applications and monitoring ML model performance.
- Data Science/AI: Applying advanced techniques in LLMs, agentic systems, vector databases, fine-tuning, and deployment tools (e.g., HuggingFace, Langchain).
- Hands-on experience working with Distributed Spark based systems
- Experience with data engineering concepts or a good understanding of data engineering concepts
- Pre-sales or post-sales experience working with external clients across a variety of industry markets. Minimum of 5+ years of customer-facing experience would be preferred
- [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets
- Communication: Proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences.
- Core Traits: Passion for lifelong learning, collaboration, and driving business value through AI.
- Education: Graduate degree in a quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research, etc) or equivalent practical experience.
- Can meet expectations for technical training and role-specific outcomes within 3 months of hire
- Can travel up to 30% when needed
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.