Artificial Intelligence Engineer

Programmers.io; Kentucky; On-site; USD 96,000 - 165,000; Full time

Job summary

Programmers.io is seeking an AI/ML Engineer for an onsite contract role in Louisville, Kentucky. The candidate will work on enterprise AI solutions, integrating and deploying AI models with governance and security in mind. Collaboration with cross-functional teams is essential to deliver production-ready capabilities.

Experience with LLMs, RAG, agent frameworks, and cloud AI platforms is highly desirable. This contract offers flexibility for C2C or W2 arrangements and requires strong

Qualifications

• Enterprise app engineering across architecture, integration, testing, deployment, and production support.
• Hands-on AI solutions using LLMs, RAG, agents, or generative AI patterns.
• Design secure, scalable solutions with governance and Responsible AI controls.
• Strong communication with business, architecture, engineering, data, security teams.
• Experience with REST APIs, microservices, event-driven architectures, secure design.

Skills

Enterprise engineering

AI/ML development

Security & governance

Stakeholder collaboration

Tools

Google Cloud Platform

Vertex AI

Azure OpenAI

LangChain

Semantic Kernel

CrewAI

OpenAI APIs

Vector databases

Job description

Programmers.io is currently looking for an \"AI/ML Engineer\"

Onsite in Louisville, Kentucky

Contract Role (Open for C2C OR W2)

Key Requirements

• Demonstrated enterprise application engineering experience, including architecture, integration, testing, deployment, and production support.


• Hands‑on experience delivering AI‑enabled solutions using LLMs, RAG, intelligent agents, or comparable Generative AI patterns.


• Ability to design secure, scalable solutions with appropriate evaluation, observability, governance, and Responsible AI controls.


• Strong communication and collaboration skills across business, architecture, engineering, data, security, and platform stakeholders.


• Cloud & AI Platforms: Google Cloud Platform, Vertex AI, Gemini models, Azure AI, Azure OpenAI, Anthropic Claude APIs, and OpenAI APIs; GECP experience where applicable


• Agentic AI: LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or comparable agent frameworks


• Generative AI: LLM endpoints, prompt engineering, embeddings, vector databases, RAG, evaluation, guardrails, and model optimization


• Enterprise Engineering: REST APIs, microservices, event‑driven architectures, enterprise integration patterns, and secure application design


• Developer Productivity: Claude Code, GitHub Copilot, Microsoft Copilot, Gemini Code Assist, GitHub, and Azure DevOps