AI Engineer

Elios, Inc.; Charlotte, Northern (NC, KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Elios, Inc. in Charlotte, NC, seeks a senior AI/ML software engineer to build production-grade GenAI apps and autonomous agents. You will design Python/FastAPI services, deploy REST APIs for LLM-driven workloads, and handle embeddings, knowledge graphs, and ontology extraction.

The role emphasizes CI/CD, evaluation, and scalable deployment across cloud platforms. The candidate brings 5+ years of AI/ML software experience and a proven track record shipping production LLM or agentic systems in

Qualifications

• 5+ years AI/ML oriented software engineering experience.
• Proven track record shipping production LLM or agentic systems.

Responsibilities

• Design and deploy Python/FastAPI services for GenAI apps.
• Build REST APIs for LLM driven applications at scale.
• Work with embeddings, knowledge graphs, and ontology extraction.
• Deploy workloads across AWS, Azure and GCP.
• Implement LLM evaluation and MLOps practices (CI/CD, testing, monitoring).
• Focus on evaluation, latency, cost, and quality in production.

Skills

GenAI development

LLM integration

Python

FastAPI

REST APIs

Docker

AWS

Azure

GCP

CI/CD

LangSmith

Ragas

Embeddings

LLMOps

MLOps

Knowledge graphs

Ontology extraction

Tools

Python

FastAPI

REST APIs

Docker

AWS

Azure

GCP

CI/CD

LangSmith

Ragas

Embeddings

LLMOps

MLOps

Knowledge graphs

Ontology extraction

Job description

GraphRAG Agentic workflows RAG Knowledge graphs Ontology extraction LLM evaluation Ragas LangSmith Embeddings LLMOps MLOps Prompt versioning Python FastAPI REST APIs Docker AWS Azure GCP CI/CD Full-stack development

Job Description

Location: Charlotte, NC | Type: Contract | Experience: 5+ years

This onsite contract role is focused on building production-grade GenAI applications and autonomous AI agents for large enterprise environments. You'll work on GraphRAG and advanced RAG architectures, enterprise data integration, and LLM-powered services that need to scale in production, not just look good in a demo.

The work includes designing and deploying Python/FastAPI services, building REST APIs for LLM-driven applications, and working with embeddings at scale, knowledge graphs, and ontology extraction. You'll also deploy workloads across AWS, Azure, and GCP.

There is a strong emphasis on evaluation and operational discipline. That includes implementing LLM evaluation frameworks with tools like Ragas and LangSmith, or custom benchmarks, to measure relevance, groundedness, and hallucination. You'll also apply LLMOps and MLOps practices such as CI/CD, prompt and version management, automated testing, and monitoring across latency, cost, and response quality.

The right person brings 5+ years of AI/ML-oriented software engineering experience and a track record of shipping production LLM or agentic systems.