Overview

In this role, you’ll work on fine-tuning Large Language Models (LLMs), applying reinforcement learning techniques, developing multi-agent systems, and leveraging Generative AI for intelligent data retrieval and visualization. Your work will enable natural language-driven insights and empower decision-making through cutting-edge AI technologies.

This is a hybrid role, and will be required to work in-office at our Plano, TX office at least 3 days per week. Candidates must be located within reasonable commuting distance of Plano, TX and be willing to work in-office on a regular basis.

Applicants must be currently authorized to work in the United States on a full-time basis and must not require sponsorship for employment visa status now or in the future.

A DAY IN THE LIFE

In this role, you will…

Build and deploy AI Agents and Tools.
Design and implement reinforcement learning algorithms and multi-agent systems to solve complex business challenges.
Develop GenAI-based solutions for intelligent data retrieval.
Collaborate with cross-functional teams—including Data Engineering, Product, and Infrastructure—to ensure secure, scalable, and efficient AI deployments.
Stay ahead of emerging trends in AI research and apply best practices to deliver innovative, business-aligned solutions.

WHO YOU ARE

You possess …

A strong technical foundation in Computer Science, Engineering, or a related field, and 2+ years of experience in AI/ML development.
Hands-on expertise in fine-tuning LLMs, reinforcement learning, multi-agent systems, and generative AI applications.
Proficiency in Python and familiarity with modern AI frameworks and cloud platforms (preferably Microsoft Azure).
Experience operationalizing AI models using MLOps best practices.
Strong problem-solving skills and the ability to translate complex technical concepts into actionable insights.
A collaborative mindset and excellent communication skills to work effectively in interdisciplinary teams.

Responsibilities

Build and deploy AI Agents for workflow automation tasks.
Develop and fine-tune LLMs for domain-specific applications.
Implement reinforcement learning algorithms and multi-agent architectures for intelligent automation.
Create GenAI-powered solutions for natural language-driven data retrieval and visualization.
Build robust MLOps pipelines for model deployment and monitoring.
Collaborate with stakeholders to align AI solutions with business objectives.
Continuously research and apply state-of-the-art AI techniques to improve system performance.
All other duties as assigned.

Qualifications

Bachelor’s degree in computer science, Engineering, or related discipline.
Project experience in LLM fine-tuning, reinforcement learning, multi-agent systems, and generative AI.
Strong programming skills in Python.
Excellent communication and collaboration skills.

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