Senior Databricks AI Platform Architect (Hybrid)

HCL Technologies Limited; Malmö kommun; Hybrid; SEK 1,100,000 - 1,700,000; Full time

Job summary

HCL Technologies Limited in Malmö seeks a Databricks expert with hands-on experience in platform setup, architecture, and AI/ML capabilities on Azure and/or GCP.

You will design and implement Databricks-based AI solutions, build Lakehouse architectures, govern access with Unity Catalog, and integrate GenAI/LLMs into end-to-end use cases, ensuring performance and security. Strong PySpark, Delta Lake, MLflow, and vector database experience are required.

Qualifications

• Needs hands-on Databricks expertise with architecture and platform setup.
• Experience building Databricks-based AI solutions and GenAI workflows.
• Strong PySpark and Delta Lake knowledge; skill with Unity Catalog and governance.

Responsibilities

• Design and implement Databricks architecture on Azure and/or GCP (workspace, clusters, networking, security).
• Lead platform setup, governance, and optimization (Unity Catalog, cost control, access management).
• Build and deploy AI/ML solutions using Databricks (MLflow, Feature Store, Model Serving).
• Develop GenAI / LLM solutions (RAG pipelines, embeddings, vector search).
• Integrate LLMs (Azure OpenAI / Vertex AI / other APIs) within Databricks.
• Deliver scalable Lakehouse architecture solutions.
• Collaborate with engineering and business teams for end-to-end AI use cases.
• Ensure performance tuning, reliability, and security of workloads.

Skills

Databricks setup

Databricks architecture

AI/ML with Databricks

MLflow

Feature Store

Model Serving

PySpark

Spark optimization

Delta Lake

Cloud platforms

LLMs / GenAI

Unity Catalog

Governance

Security

LangChain

Vector databases

Job description

HCL Technologies Limited in Malmö seeks a Databricks expert with hands-on experience in platform setup, architecture, and AI/ML capabilities on Azure and/or GCP.

You will design and implement Databricks-based AI solutions, build Lakehouse architectures, govern access with Unity Catalog, and integrate GenAI/LLMs into end-to-end use cases, ensuring performance and security. Strong PySpark, Delta Lake, MLflow, and vector database experience are required.