Generative AI Engineer - Irving, TX

  • Irving, TX
  • Posted 13 hours ago | Updated 13 hours ago

Overview

Hybrid
Depends on Experience
Contract - Independent
Contract - W2

Skills

Amazon Web Services
Analytical Skill
Artificial Intelligence
Autogen
Cloud Computing
Collaboration
Conflict Resolution
Continuous Delivery
Continuous Integration
Decision-making
Django
Docker
FOCUS
Flask
Generative Artificial Intelligence (AI)
Good Clinical Practice
Google Cloud Platform
Kubernetes
LangChain
Large Language Models (LLMs)
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Microsoft Azure
Problem Solving
Python
Regulatory Compliance
PyTorch
Research
Scalability
TensorFlow
User Experience
Vector Databases
scikit-learn

Job Details

Generative AI Engineer

Location: Irving, TX

Job Overview

We are seeking a highly skilled AI Engineer with strong expertise in Agent Development, Large Language Models (LLMs), and Python. In this role, you will design, build, and deploy intelligent AI/ML solutions that drive automation, improve decision-making, and enhance user experience.

Key Responsibilities

Design and develop AI/ML applications with a focus on agent-based systems and LLM integration.

Build, fine-tune, and optimize machine learning models for production environments.

Develop robust and scalable APIs and backend services in Python.

Collaborate with data engineers, software developers, and product managers to deliver end-to-end AI solutions.

Research and evaluate emerging AI/ML frameworks, tools, and methodologies to improve solution effectiveness.

Ensure security, scalability, and performance of deployed models and AI services.

Required Skills & Qualifications

Strong programming experience in Python (FastAPI, Flask, or Django a plus).

Hands-on experience with Large Language Models (LLMs) such as OpenAI, Hugging Face, or similar.

Proficiency with agent development frameworks (LangChain, AutoGen, or equivalent).

Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

Familiarity with cloud platforms (AWS, Google Cloud Platform, Azure) and containerization (Docker/Kubernetes).

Strong analytical and problem-solving skills with the ability to work independently and in team settings.

Nice to Have

Experience in AI security and compliance in cloud-native environments.

Familiarity with vector databases (Pinecone, Weaviate, FAISS).

Exposure to MLOps tools and practices (CI/CD pipelines, model monitoring, etc.).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.