AI Engineer

Precinmac•Indianapolis, IN

60d•Onsite

About The Position

This role is required to be onsite. The AI Engineer is an experienced technical professional who bridges business strategy with AI technology to design and implement scalable, secure AI systems to meet organizational goals. Collaboratively work with others in various areas of the company to identify appropriate use of AI, within CMMC regulations. Create blueprints for AI applications, select appropriate AI models, data pipelines and infrastructure to develop end to end AI systems.

Requirements

Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or Engineering.
Five years or more experience deploying AI solutions at scale.
Experience with Generative AI, AI Agents, or Reinforcement Learning
Python proficiency and experience with major ML frameworks and AI platforms
Experience in a regulated manufacturing, aerospace, or defense environment highly desired.
Experience with MES/ERP systems, quality management systems, and manufacturing data preferred.
NLP/document AI
Strong analytical and problem-solving skills, with knowledge of forecasting and data modeling.
Experience with handling unstructured data, including images, videos, and text.
A proactive mindset with the drive to turn ideas into measurable outcomes.
Experience developing data and machine learning-based solutions and deploying them to production with many users
Ability to simplify complex technical concepts and influence technical and business stakeholders.
Strong foundational knowledge of enterprise data architecture, including data modeling (conceptual, logical, physical), metadata management, master data management (MDM), and data integration patterns.

Responsibilities

Develop understanding of the business operations to integrate with AI technology solutions.
Provide expertise in collaboration with stakeholders to create solutions that improve business processes and efficiencies.
Ensure proper data handling, model training infrastructure and deployment.
Influence AI strategy and help drive AI adoption.
Establish secure, scalable, and responsible AI architecture standards, within a CMMC certified environment.
Integrate AI systems with existing IT infrastructure and ensure seamless operation.
Ensure AI system designs align with enterprise data models, data governance policies, data retention standards, and lineage requirements.
Design solutions that integrate various systems and technologies to meet business objectives.
Understand business problems and identify opportunities to implement data science solutions.
Architect end to end data flows, ensuring high quality data ingestion, transformation, storage, and retrieval across structured, semi structured, and unstructured data sources.
Design AI powered and GenAI enabled applications and services to support business processes by collaborating with stakeholders, including Engineering, Operations, support functions, and other IT professionals.
Design, develop, and deploy machine learning models and algorithms from proof of concept through production deployment.
Develop, verify, and validate analytics to address business needs and opportunities.
Apply lean methodologies to identify opportunities for process improvement.