AI Engineer

Zeus

AI Engineer responsible for designing AI solutions to enhance manufacturing workflows at Zeus Industrial Products. Collaborating with data scientists and stakeholders to operationalize AI integrations.

Posted 6/12/2026full-timeRemote • South Carolina • 🇺🇸 United StatesMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudERPPython

About the role

Key responsibilities & impact

Design, develop, and deploy enterprise AI applications, AI agents, copilots, and intelligent workflow solutions across manufacturing and corporate domains.
Build and maintain AI orchestration pipelines utilizing LLMs, retrieval-augmented generation (RAG), vector search, prompt frameworks, and agent-based architectures.
Develop scalable AI integration patterns between enterprise platforms such as Snowflake, Salesforce, ERP systems, SCADA/OT systems, document repositories, and collaboration platforms.
Collaborate with data scientists and business stakeholders to operationalize machine learning and generative AI solutions into production environments.
Design APIs, middleware, and integration services supporting AI-driven automation and cross platform communication.
Develop and optimize semantic search, enterprise knowledge retrieval, and conversational AI capabilities.
Support the implementation of AI governance, security, observability, model evaluation, and human-in-the-loop approval processes.
Drive enterprise AI architecture strategy and standards, partnering across teams to define approaches for AI platforms, orchestration, deployment, and lifecycle management.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI, or related technical discipline.
6+ years of experience in software engineering, AI engineering, machine learning engineering, or related technical roles.
Strong proficiency in Python and experience developing APIs, backend services, and automation frameworks.
Hands-on experience with LLMs, prompt engineering, AI agents, RAG architectures, and vector databases/search technologies.
Experience with modern AI frameworks and orchestration tools (LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar).
Experience integrating enterprise systems using REST APIs, event-driven architectures, or middleware platforms.
Familiarity with cloud and data platforms such as Snowflake, Azure, AWS, Databricks, or similar ecosystems.
Strong understanding of software engineering best practices including Git, CI/CD, testing, monitoring, and deployment pipelines.
Excellent communication and cross-functional collaboration skills.
Preferred Qualifications include a Master’s degree in Computer Science, Software Engineering, Data Science, AI, or related technical discipline.

Benefits

Comp & perks

Competitive pay
Great benefits package

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonAPIsAI orchestration pipelinesLLMsprompt engineeringRAG architecturesvector databasesautomation frameworkssoftware engineering best practicesmachine learning engineering

Soft Skills

communicationcross-functional collaboration

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in Software EngineeringBachelor’s degree in Data ScienceBachelor’s degree in AIMaster’s degree in Computer ScienceMaster’s degree in Software EngineeringMaster’s degree in Data ScienceMaster’s degree in AI