Azure Databricks Engineer – GenAI

Infosys Pontoon•Minneapolis, MN

2d•Onsite

About The Position

The Azure Databricks Engineer – GenAI will design, build, and maintain scalable, secure, high-performance data pipelines and enterprise applications using Azure Databricks, .NET, Azure, and Generative AI technologies. The role supports batch and streaming data workloads, cloud-native data platform modernization, reliable ingestion and transformation of enterprise data, and AI-powered business solutions. The engineer will collaborate with data domain experts across Operations, Product, Finance, Value Analytics, and other areas to develop connected data models and trusted datasets for reporting, analytics, and downstream consumers. The role also partners with AI/ML engineers and leads to build or improve machine learning models and experiment with novel ML and Generative AI architectures, including capabilities such as conversational assistants, intelligent search, summarization, content generation, and workflow automation. The position is onsite in Hartford, Connecticut, or Minnetonka, Minnesota, and is listed for a six-month duration.

Requirements

4 to 6 years of experience.
Azure Databricks skills and knowledge of Generative AI technologies, including LLMs, RAG, AI Agents, Vector Databases, and Prompt Engineering.
Top listed responsibilities/skills include Azure Databricks, PySpark, and Python.

Nice To Haves

One year of experience working with LLMs, RAG, AI Agents, Vector Databases, and Prompt Engineering.
Experience developing AI-driven solutions using GitHub Copilot, Microsoft 365 Copilot, Azure AI Studio, and enterprise GenAI platforms.
Experience in the healthcare domain.
.NET.

Responsibilities

Design, build, and maintain scalable, secure, high-performance batch and streaming data pipelines using modern data engineering practices.
Lead modernization and migration of on-premise data platforms to cloud-native architectures, including infrastructure, networking, security, and deployment pipelines.
Develop and maintain data platform components for reliable ingestion, transformation, enrichment, and consumption of enterprise data.
Collaborate with data domain experts across Operations, Product, Finance, Value Analytics, and other domains to understand data sources and design efficient, connected data models.
Implement validation, monitoring, documentation, and security controls to support data accuracy, quality, relevance, and governance.
Analyze large datasets to identify trends, patterns, and actionable insights supporting analytics, AI use cases, and business strategy.
Make curated, trusted datasets available to BI and downstream consumers for reporting and analytics.
Partner with AI/ML engineers and leads to design, build, and improve machine learning models.
Contribute to experimentation with novel machine learning and Generative AI architectures.
Help design and implement AI-powered enterprise applications.
Design, develop, and maintain scalable enterprise applications and AI-powered solutions using .NET, Azure, and Generative AI technologies.
Build and integrate AI capabilities such as conversational assistants, intelligent search, summarization, content generation, and workflow automation into business applications.
Implement secure, reliable, high-performing software solutions that adhere to enterprise architecture, compliance, and governance standards.
Drive continuous improvement through automation, AI-assisted development practices, code quality enhancements, and operational excellence initiatives.
Analyze and investigate.