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Generative AI Engineer

XPath Solutions
Full-time
On-site
Dallas, Texas, United States
Job Description

Job Description Location Dallas, TX (or) Charlotte, NC (or) Raleigh, NC

US Citizens and Green Card Holders needed

Role Overview We are seeking a highly skilled

Generative AI Engineer

with a strong

Python background

to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with

Large Language Models (LLMs) ,

prompt engineering , and

Generative AI frameworks , along with proven expertise in building

scalable AI applications

for enterprise use cases.

This role focuses on developing

agentic AI systems , retrieval-augmented generation (RAG), and multi modal AI solutions while integrating GenAI capabilities into production-grade applications and workflows.

Mission Design and deliver

scalable, production-ready Generative AI solutions

that leverage modern LLMs, agentic frameworks, and cloud AI platforms to power intelligent applications across the enterprise.

Key Responsibilities (Scope) Design and implement

Generative AI models

for:

Text-based applications

Image-based applications

Multimodal AI solutions

Develop and optimize

prompt engineering strategies

to improve LLM performance and reliability

Build and integrate

embedding-based retrieval systems

and

RAG pipelines

Integrate Generative AI capabilities into

web applications and enterprise workflows

Design and develop

agentic AI applications

with:

Context management

Session and memory handling

MCP (Model Context Protocol) tools

Collaborate with cross-functional teams to deploy AI solutions at scale

Ensure AI solutions are reliable, secure, and production-ready

Required Qualifications Strong proficiency in

Python

Solid experience with

AI/ML frameworks

such as:

PyTorch

TensorFlow

Hands-on experience building

multi-agent systems , including:

Session management

Memory handling

MCP tools

Practical experience working with:

Large Language Models (LLMs)

Transformer architectures

Hugging Face ecosystem

Knowledge and experience with:

Vector databases

Retrieval-Augmented Generation (RAG)

Semantic search techniques

Familiarity with

cloud AI services , including:

AWS SageMaker

Azure OpenAI

GCP Vertex AI

Understanding of

MLOps practices

for scalable AI deployment

Preferred Qualifications Knowledge of

AI ethics , including:

Bias mitigation

Responsible AI practices

Experience designing AI systems with governance, transparency, and compliance in mind

Apply now
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