AI Engineer

VDart; Frisco (TX); On-site; Full time

Job summary

A leading technology firm is seeking a Mid-Senior AI Engineer to architect and deploy intelligent systems using advanced techniques like RAG and Large Language Models. The ideal candidate will have extensive experience in full-stack development and a strong focus on generative AI. Responsibilities include designing RAG pipelines, applying chunking strategies, and collaborating on scalable AI solutions. Candidates should possess deep expertise in Python and relevant MLOps tools. This contract position is based in Frisco, TX.

Qualifications

• 8 to 12 years of experience as a Full‑stack developer.
• At least 2 to 4 years in generative AI or RAG systems.
• Experience with MLOps tools: MLflow, Docker, CI/CD.

Responsibilities

• Design and implement RAG pipelines.
• Apply chunking strategies for optimization.
• Finetune and evaluate LLMs for various tasks.
• Build multi‑agentic systems.
• Integrate AI capabilities into enterprise applications.
• Collaborate with stakeholders for scalable solutions.
• Ensure model reliability and ethical compliance.

Skills

Full-stack development

Generative AI or RAG systems

Chunking techniques

Embedding strategies

MLflow

Docker

CI/CD pipelines

Prompt engineering

Model evaluation

Python

AI solutions

SDLC lifecycle

Partner client communications

Job description

Location: Frisco, TX and Bellevue, WA

Employment type: Contract Position

Overview

We are seeking a forward‑thinking AI Engineer to architect and deploy intelligent systems powered by Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), and advanced chunking strategies. This role is ideal for engineers passionate about building scalable, production‑grade AI applications that leverage cutting‑edge retrieval and generation techniques.

Role Description

• Design and implement RAG pipelines using hybrid search, vector keyword, semantic ranking, and metadata enrichment.
• Apply chunking strategies (fixed‑size, recursive, semantic, agentic) to optimize document segmentation for retrieval and embedding.
• Finetune and evaluate LLMs (e.g., GPT, LLaMA, Ollama) for tasks such as QA, summarization, NER, and sentiment analysis.
• Build multi‑agentic systems.
• Integrate AI capabilities into enterprise applications using Azure OpenAI, Cognitive Search, Azure Functions, and Power Automate.
• Collaborate with stakeholders to translate business needs into scalable AI solutions.
• Ensure model reliability, performance, and ethical compliance across deployments.

Skills

• 8 to 12 years of experience as a Full‑stack developer with at least 2 to 4 years in generative AI or RAG systems.
• Chunking techniques and embedding strategies.
• MLOps tools: MLflow, Docker, CI/CD pipelines.
• Experience with prompt engineering and model evaluation.
• Mandatory familiarity with agentic systems and multi‑agent orchestration.
• Technical soft skills: Expertise level Expert, Good Knowledge.
• Python – Expert.
• AI solutions – Expert.
• SDLC lifecycle – Good.
• Partner client communications – Expert.

Desired Skills

• Technical soft skills: Expertise level Expert, Good Knowledge.

Seniority Level

Mid‑Senior level

Employment type

Contract

Job function

Information Technology

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