AI Engineer

Elios, Inc.; Dallas (TX); Hybrid; USD 120,000 - 150,000; Full time

Job summary

Elios, Inc. is hiring an AI Engineer for a hands-on, onsite contract in Dallas to build production GenAI applications and autonomous agents connected to enterprise data. You will design, build, and deploy LLM-powered services with Python, FastAPI, and Docker across AWS, Azure, and GCP.

You will establish evaluation workflows and CI/CD, focusing on latency, cost, and accuracy. Ideal candidates have 5+ years of AI/ML software experience, shipped production LLMs or agents, and strong skills in

Qualifications

• At least 5 years of AI/ML-focused software engineering experience.
• Shipped production LLM or agentic AI systems beyond demos.
• Strong experience with embeddings, knowledge graphs, ontology extraction.
• Hands-on with Python, FastAPI, Docker, and cloud deployments (AWS/Azure/GCP).
• Experience with CI/CD, automated testing, and monitoring for latency and cost.

Responsibilities

• Build production GenAI applications and autonomous AI agents connected to enterprise data.
• Develop scalable Python services and REST APIs using FastAPI.
• Deploy workloads with Docker across AWS, Azure, and GCP.
• Set up LLM evaluation workflows using LangSmith and Ragas benchmarks.
• Lead MLOps practices, including CI/CD, version management, and monitoring.

Skills

GenAI architectures

Embeddings

Knowledge graphs

Ontology extraction

Python

FastAPI

Docker

AWS

Azure

GCP

CI/CD

REST APIs

MLOps

On-site engineering

Llama/agents

Education

5+ years AI/ML software engineering

Tools

LangSmith

Ragas

Job description

GraphRAG Agent orchestration RAG LLMOps LangSmith Ragas Knowledge graphs Ontology extraction Embeddings FastAPI LLM evaluation Enterprise data integration Python Docker AWS Azure GCP CI/CD REST APIs MLOps Full-stack development

Job Description

We're hiring an AI Engineer for a contract role in Dallas, Texas. This is a hands-on, onsite position focused on building production GenAI applications and agentic systems that connect to enterprise data and reach end users in real operating environments. You'll design, build, and deploy LLM-powered applications and autonomous AI agents, with a strong focus on GraphRAG, advanced RAG architectures, and enterprise-grade reliability.

The work includes building GenAI services in Python with FastAPI, developing scalable REST APIs, deploying workloads with Docker across AWS, Azure, and GCP, and supporting full-stack delivery when needed. You'll also set up LLM evaluation workflows using tools such as Ragas, LangSmith, and custom benchmarks to measure groundedness, relevance, and hallucination rates.

This role also covers LLMOps and MLOps practices, including CI/CD, prompt and version management, automated testing, and monitoring for latency, cost, and response quality. The right person brings at least 5 years of AI/ML-focused software engineering experience and has shipped production LLM or agentic AI systems that made it past the demo stage. Strong experience with embeddings, knowledge graphs, ontology extraction, and enterprise data integration is important, along with the ability to help shape architecture and delivery standards for modern GenAI systems.