Job Title: Data Scientist (Generative AI / Agentic AI) Location: Plano TX/Oklahoma City OK/Little Rock AR/Springfield MO/Denver CO Can do Only W2 No C2C
Job Summary:
We are seeking an experienced Data Scientist with expertise in Generative AI and Agentic AI to join a high-impact initiative based in Plano TX. The ideal candidate will possess strong hands-on experience as an Individual Contributor in Machine Learning Engineering and have deep knowledge of modern AI architectures LLM-powered applications MLOps and cloud platforms. This role requires collaboration with cross-functional AI teams to build scalable production-grade intelligent systems.
Key Responsibilities:
Design develop and deploy advanced Machine Learning and Generative AI solutions.
Build and support Agentic AI architectures including multi-agent systems and agent-based workflows.
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines and LLM-powered applications.
Implement Model Context Protocol (MCP) and context engineering techniques to improve AI system performance.
Design and orchestrate AI workflows using modern AI orchestration frameworks.
Apply advanced prompting methodologies including Chain-of-Thought (CoT) Tree-of-Thought (ToT) and Graph-of-Thought (GoT) reasoning frameworks.
Collaborate with Machine Learning Engineers Data Scientists and AI practitioners to deliver scalable AI solutions.
Build and maintain MLOps pipelines supporting model lifecycle management CI/CD monitoring and automation.
Support software development best practices including code reviews version control and collaborative development workflows.
Work with cloud-native AI and data platforms to deploy and manage production workloads.
Participate in Agile/Scrum ceremonies and contribute to end-to-end SDLC activities.
Collaborate with data engineering teams to support scalable data pipelines and feature engineering processes.
Required Skills:
10 years of hands-on experience in Machine Learning Engineering as an Individual Contributor
Strong expertise in Generative AI
Deep understanding of Agentic AI Architectures
Experience with:
Agent-Based Workflows
Multi-Agent Systems
AI Orchestration
Hands-on experience with:
Model Context Protocol (MCP)
Retrieval-Augmented Generation (RAG)
Context Engineering
LLM-powered applications
Strong knowledge of advanced prompting techniques:
Chain-of-Thought (CoT)
Tree-of-Thought (ToT)
Graph-of-Thought (GoT)
Expertise in MLOps
Experience with:
Model Lifecycle Management
CI/CD Pipelines
Model Monitoring
Automation
Strong experience with cloud platforms preferably:
Google Cloud Platform (GCP)
Exposure to:
Microsoft Azure
Amazon Web Services (AWS)
Proficiency with:
GitHub
Version Control Systems
Code Review Processes
Collaborative Software Development Workflows
Strong understanding of:
SDLC
Agile/Scrum methodologies
Data Engineering concepts
Preferred Qualifications:
Experience building enterprise-scale LLM and GenAI solutions.
Experience with AI agent frameworks and orchestration platforms.
Experience designing scalable production-grade AI systems.
Exposure to vector databases and semantic search technologies.
Experience working with cloud-native AI services.
Knowledge of responsible AI model governance and AI security practices.
Familiarity with distributed systems and microservices architectures.
Experience supporting large-scale AI initiatives in enterprise environments.
Job Title: Data Scientist (Generative AI / Agentic AI) Location: Plano TX/Oklahoma City OK/Little Rock AR/Springfield MO/Denver CO Can do Only W2 No C2C Job Summary: We are seeking an experienced Data Scientist with expertise in Generative AI and Agentic AI to join a high-impact initiative based in...
Job Title: Data Scientist (Generative AI / Agentic AI) Location: Plano TX/Oklahoma City OK/Little Rock AR/Springfield MO/Denver CO Can do Only W2 No C2C
Job Summary:
We are seeking an experienced Data Scientist with expertise in Generative AI and Agentic AI to join a high-impact initiative based in Plano TX. The ideal candidate will possess strong hands-on experience as an Individual Contributor in Machine Learning Engineering and have deep knowledge of modern AI architectures LLM-powered applications MLOps and cloud platforms. This role requires collaboration with cross-functional AI teams to build scalable production-grade intelligent systems.
Key Responsibilities:
Design develop and deploy advanced Machine Learning and Generative AI solutions.
Build and support Agentic AI architectures including multi-agent systems and agent-based workflows.
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines and LLM-powered applications.
Implement Model Context Protocol (MCP) and context engineering techniques to improve AI system performance.
Design and orchestrate AI workflows using modern AI orchestration frameworks.
Apply advanced prompting methodologies including Chain-of-Thought (CoT) Tree-of-Thought (ToT) and Graph-of-Thought (GoT) reasoning frameworks.
Collaborate with Machine Learning Engineers Data Scientists and AI practitioners to deliver scalable AI solutions.
Build and maintain MLOps pipelines supporting model lifecycle management CI/CD monitoring and automation.
Support software development best practices including code reviews version control and collaborative development workflows.
Work with cloud-native AI and data platforms to deploy and manage production workloads.
Participate in Agile/Scrum ceremonies and contribute to end-to-end SDLC activities.
Collaborate with data engineering teams to support scalable data pipelines and feature engineering processes.
Required Skills:
10 years of hands-on experience in Machine Learning Engineering as an Individual Contributor
Strong expertise in Generative AI
Deep understanding of Agentic AI Architectures
Experience with:
Agent-Based Workflows
Multi-Agent Systems
AI Orchestration
Hands-on experience with:
Model Context Protocol (MCP)
Retrieval-Augmented Generation (RAG)
Context Engineering
LLM-powered applications
Strong knowledge of advanced prompting techniques:
Chain-of-Thought (CoT)
Tree-of-Thought (ToT)
Graph-of-Thought (GoT)
Expertise in MLOps
Experience with:
Model Lifecycle Management
CI/CD Pipelines
Model Monitoring
Automation
Strong experience with cloud platforms preferably:
Google Cloud Platform (GCP)
Exposure to:
Microsoft Azure
Amazon Web Services (AWS)
Proficiency with:
GitHub
Version Control Systems
Code Review Processes
Collaborative Software Development Workflows
Strong understanding of:
SDLC
Agile/Scrum methodologies
Data Engineering concepts
Preferred Qualifications:
Experience building enterprise-scale LLM and GenAI solutions.
Experience with AI agent frameworks and orchestration platforms.
Experience designing scalable production-grade AI systems.
Exposure to vector databases and semantic search technologies.
Experience working with cloud-native AI services.
Knowledge of responsible AI model governance and AI security practices.
Familiarity with distributed systems and microservices architectures.
Experience supporting large-scale AI initiatives in enterprise environments.