AI Engineer

Propertyvalue Prudent Technologies And Consulting

Minneapolis, MN, United States

21 days ago

Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

2 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Microsoft Azure Cloud Computing Human-Computer Interaction Machine Learning Tensorflow Reinforcement Learning Azure Data Factory Pytorch Large Language Models Generative AI Backend

+4 more

AI Platforms Front End Software Development Virtual Agents Databricks

Job description

Build and experiment with GenAI models and agentic workflows, contributing to the development of intelligent security solutions.
Collaborate across the stack, supporting backend services, model pipelines, and frontend interfaces for agentic systems.
Prototype rapidly, iterate on ideas, and contribute to incubation efforts in a startup-style environment.
Work closely with senior engineers and researchers, learning best practices and contributing to production-grade AI systems

Requirements

3 years of hands-on experience with machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar).
2 years of hands-on experience in developing and deploying AI agents and machine learning models.
·Machine learning frameworks and libraries (such as TensorFlow, PyTorch, or similar), developing and deploying AI agents and machine learning models, Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Azure, including expertise in Azure Data and AI platforms (such as Databricks, Fabric, and AI Foundry), Build and experiment with GenAI models and agentic workflows
·Design and implement intelligent AI agents leveraging large language models (LLMs), planning algorithms, and decision-making frameworks.
Build secure, scalable AI agents and integrate into applications and workflows for robust, cross-platform deployment and enhanced user experience.
Advance AI agent capabilities through research and performance evaluation, focusing on improved conversation, decision-making, adaptability, and the implementation of safety and guardrail mechanisms.
Continuously optimize agent performance through feedback mechanisms, reinforcement learning, and user interaction analysis.
Demonstrate deep expertise in cloud technologies, with a strong focus on Microsoft Azure, including expertise in Azure Data and AI platforms (such as Databricks, Fabric, and Microsoft AI Foundry).