Principal AI Engineer

DPR•Dallas, TX

About The Position

Join a dynamic and fast-evolving team that is building next-generation AI-based tools and agent systems for the construction Industry. Our AI and Data Team is focused on designing intelligent AI agents, and copilots using modern AI/ML techniques. You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.

Requirements

At least 3 years of experience with Software Development, Machine Learning.
At least 2 years of experience Generative AI, specifically with Large Language Models (LLM)
Excellent knowledge of machine learning algorithms, deep learning frameworks (e.g. Tensorflow, Pytorch), and statistical methods.
Experience with generative AI concepts such as Retrieval-Augmented Generation (RAG), agentic workflows, training LLMs with structured and unstructured data sets
Experience with Data Connectors and API gateways that support seamless communication between systems.
Deep subject matter expertise in AI technologies, including but not limited to Copilot Studio, OpenAI, Semantic Kernels, Azure AI Foundry, Google Gemini, Microsoft 365, and M365 Copilot or Anthropic or AWS platforms.
Familiarity with cloud environments (e.g., AWS, Azure, GCP) and MLOps tools.
Strong programming skills in Python and experience with AI/ML frameworks
Proficiency in vector databases and embedding models for retrieval tasks
Possess strong problem-solving and strategic thinking abilities.

Nice To Haves

Understanding of Knowledge Graph is a plus

Responsibilities

Architecture and design: Lead the design of AI/ML infrastructure, platforms, and services, ensuring they are reliable, performant, and scalable.
End-to-end development: Own the entire lifecycle of AI projects, including prompt engineering, workflow design, model deployment, and A/B testing.
Technical leadership: Mentor and guide teams, hold a high technical bar for solutions, and partner with other senior engineers to align technical solutions with business needs.
Implementation: Write code in languages like Python, build APIs and microservices, and integrate AI/ML models into existing systems.
Continuous learning: Stay current with rapidly evolving AI technologies, such as LLMs and agentic AI patterns.
Collaboration: Work with cross-functional teams, including product managers, Business users, and security teams, to deliver AI-powered products.
Problem-solving: Apply strong analytical and problem-solving skills to address complex technical challenges.
Integrate AI: Assist in the development and execute comprehensive plans to integrate AI technologies into business processes, aimed at enhancing operational efficiency and boosting employee productivity.
AI Rollout: Ensure the scalability, reliability, and security of AI solutions by implementing best practices for AI model development, deployment, and maintenance.

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