AI Engineer

This is a fully remote position, open to applicants in South Carolina.

📋 Description

• Design, develop, and implement enterprise AI applications, AI agents, copilots, and intelligent workflow solutions within manufacturing and corporate sectors.

• Construct and sustain AI orchestration pipelines using LLMs, retrieval-augmented generation (RAG), vector search, prompt frameworks, and agent-based architectures.

• Create scalable AI integration patterns that connect enterprise platforms such as Snowflake, Salesforce, ERP systems, SCADA/OT systems, document repositories, and collaboration tools.

• Work alongside data scientists and business stakeholders to operationalize machine learning and generative AI solutions in production settings.

• Design APIs, middleware, and integration services that facilitate AI-driven automation and cross-platform communication.

• Develop and enhance semantic search, enterprise knowledge retrieval, and conversational AI functionalities.

• Assist in the implementation of AI governance, security, observability, model evaluation, and human-in-the-loop approval processes.

• Lead the enterprise AI architecture strategy and standards, collaborating with various teams to establish methodologies for AI platforms, orchestration, deployment, and lifecycle management.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, AI, or a related technical field.

• Over 6 years of experience in software engineering, AI engineering, machine learning engineering, or similar technical positions.

• Strong expertise in Python with experience in developing APIs, backend services, and automation frameworks.

• Practical experience with LLMs, prompt engineering, AI agents, RAG architectures, and vector databases/search technologies.

• Familiarity with contemporary AI frameworks and orchestration tools (LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or comparable).

• Experience in integrating enterprise systems through REST APIs, event-driven architectures, or middleware platforms.

• Knowledge of cloud and data platforms such as Snowflake, Azure, AWS, Databricks, or similar ecosystems.

• Strong grasp of software engineering best practices, including Git, CI/CD, testing, monitoring, and deployment pipelines.

• Exceptional communication and cross-functional collaboration abilities.

• Preferred qualifications include a Master’s degree in Computer Science, Software Engineering, Data Science, AI, or a related technical discipline.

🏝️ Benefits

• Competitive compensation

• Comprehensive benefits package