TechShack is back delivering on a Databricks Enterprise programme with a leading European Databricks consultancy. We’ve already helped scale this project, and as it continues to grow we’re looking for senior, hands-on Solutions Architects who can take GenAI past proof of concept and into reliable production systems.

The role

You’ll be the technical lead for major enterprise clients, designing and building data platforms and GenAI applications on Databricks. You’ll put the operational foundations in place to keep them running well and act as a trusted advisor to client stakeholders. You’ll go through official Databricks RSA vetting and report into Databricks.

What you’ll be doing

• Leading end-to-end delivery of data pipelines and GenAI applications on Databricks (retrieval, agents, natural-language-to-data)
• Building MLOps and LLMOps foundations: CI/CD, model serving, monitoring and evaluation
• Tuning Spark workloads and LLM inference for performance, latency and cost
• Partnering long term with enterprise clients to turn business challenges into scalable architecture
• Setting engineering standards and best practice across client teams

What you’ll need

• Databricks certification (required, Data Engineer Professional preferred)
• Senior, hands-on Apache Spark experience in Python or Scala
• Strong Databricks Lakehouse architecture and delivery experience
• Performance engineering at scale: query tuning and debugging distributed systems
• Production delivery of RAG, agentic and tool-calling LLM applications
• Modern GenAI frameworks such as LangChain, DSPy or Hugging Face
• Hands-on MLflow, model serving and AI monitoring
• CI/CD, testing for AI and infrastructure-as-code
• Confident working with senior client stakeholders

Nice to have

• Vetted by Databricks within the last 12 months (a big bonus)
• Previous Databricks RSA, Professional Services or partner delivery experience
• Mosaic AI, Vector Search, Unity Catalog and Model Serving
• Consultancy background with large enterprise clients

The details

Fully remote

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• Databricks certification (required, Data Engineer Professional preferred)
• Senior, hands-on Apache Spark experience in Python or Scala
• Strong Databricks Lakehouse architecture and delivery experience
• Performance engineering at scale: query tuning and debugging distributed systems
• Production delivery of RAG, agentic and tool-calling LLM applications
• Modern GenAI frameworks such as LangChain, DSPy or Hugging Face
• Hands-on MLflow, model serving and AI monitoring
• CI/CD, testing for AI and infrastructure-as-code
• Confident working with senior client stakeholders

Nice to have

• Vetted by Databricks within the last 12 months (a big bonus)
• Previous Databricks RSA, Professional Services or partner delivery experience
• Mosaic AI, Vector Search, Unity Catalog and Model Serving
• Consultancy background with large enterprise clients

TechShack is back delivering on a Databricks Enterprise programme with a leading European Databricks consultancy. We’ve already helped scale this project, and as it continues to grow we’re looking for senior, hands-on Solutions Architects who can take GenAI past proof of concept and into reliable production systems.