AI Software Engineer

ERP Suites•Loveland, OH

1d•Remote

About The Position

ERP Suites is seeking AI Software Engineers to join our growing team and contribute to the development of innovative AI solutions, both productized and custom. This role is ideal for individuals who thrive in a collaborative environment while also demonstrating strong ownership, attention to detail, and the ability to deliver high-quality solutions independently. At ERP Suites, we pride ourselves on delivering innovative, scalable solutions and providing exceptional, first-class support to our customers. Role Overview: As an AI Software Engineer, you will design, develop, deploy, and support AI-powered applications that solve real business challenges. This role blends software engineering, AI/ML implementation, systems integration, and production support to ensure solutions are reliable, secure, scalable, and aligned with business objectives. Location: Our home office is based in Cincinnati, OH. However, we are open to hiring someone who is fully remote regardless of location. Although the position will be remote, there might be some occasional travel to ERPS facilities or customer sites.

Requirements

Bachelor’s degree in computer science, Information Technology, or a related field.
1–3+ years of experience working with AI platforms such as Oracle AI, AWS AI, Anthropic, or OpenAI.
Proficiency in Python.
Strong understanding of (LLMs)

Nice To Haves

Experience with LangChain, vector databases, RAG, or MCP frameworks.
Familiarity with OCI and Docker.

Responsibilities

Design and develop AI-enabled applications, services, APIs, and workflows.
Translate business requirements into technical AI solutions and system designs.
Build and maintain integrations between AI services and enterprise systems.
Prepare, manage, and validate data for AI models and inference workflows .
Optimize prompt engineering, retrieval logic, orchestration flows, and agent behavior .
Deploy AI solutions using best practices in software engineering and DevOps.
Monitor performance, reliability, output quality, latency, and cost in production environments.
Troubleshoot and resolve system defects, performance issues, and integration challenges.
Ensure AI systems meet security, governance, privacy, and compliance standards.
Document architectures, workflows, technical decisions, and support procedures .
Collaborate cross-functionally to deliver measurable business value.
Continuously improve solutions based on performance data and user feedback.