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Model Context Protocol Jobs in Texas (NOW HIRING)

You will integrate these agents into our Microservices Architecture and leverage the Model Context Protocol (MCP) to connect LLMs seamlessly with enterprise data sources, development environments ...

Build and maintain Model Context Protocol (MCP) servers and clients to securely expose data, file systems, and enterprise tools to LLMs. * Microservices Integration: Wrap AI agents, RAG engines, and ...

Security Architect

Dallas, TX · Hybrid

$90 - $100/hr

Hands-on experience securing Generative AI, Agentic AI, Large Language Models (LLMs), Model Context Protocol (MCP), and AI APIs--especially within AWS cloud environments. Framework Proficiency:

New

In this role, you will champion our transition to AI-first engineering practices by actively integrating Agentic AI, Model Context Protocol (MCP), and approved AI tools into the software development ...

Senior Professional, Software Engineer

Dallas, TX · On-site

$121K - $159K/yr

In this role, you will champion our transition to AI-first engineering practices by actively integrating Agentic AI, Model Context Protocol (MCP), and approved AI tools into the software development ...

Agentic AI Engineer

Dallas, TX · On-site

$120K - $140K/yr

Design and integrate Model Context Protocol (MCP) clients and tool ecosystems. * Build conversational AI applications with contextual memory, reasoning, and dynamic tool invocation. * Develop and ...

Agentic AI Engineer

Dallas, TX · On-site

$150 - $200/hr

Design and integrate Model Context Protocol (MCP) clients and tool ecosystems. * Build conversational AI applications with contextual memory, reasoning, and dynamic tool invocation. * Develop and ...

Agentic AI Engineer

Dallas, TX · On-site

$150 - $210/hr

Design and integrate Model Context Protocol (MCP) clients and tool ecosystems. * Build conversational AI applications with contextual memory, reasoning, and dynamic tool invocation. * Develop and ...

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Model Context Protocol information

What is the difference between Model Context Protocol vs Data Analyst?

AspectModel Context ProtocolData Analyst
Required CredentialsKnowledge of data modeling, API protocols, and software developmentBachelor's degree in statistics, mathematics, or related field
Work EnvironmentTechnical teams, software development, AI/ML projectsBusiness intelligence, reporting, data visualization
Industry UsageTech, AI, software developmentFinance, marketing, healthcare, business
Search & Comparison IntentUnderstanding technical protocols for AI modelsAnalyzing data for insights and decision-making

The Model Context Protocol focuses on technical data exchange and AI model integration, requiring programming and API knowledge. In contrast, Data Analysts interpret data to generate reports and insights, often working with business tools. Both roles involve data but serve different functions within organizations.

What are popular job titles related to Model Context Protocol jobs in Texas?

For Model Context Protocol jobs in Texas, the most frequently searched job titles are:

What cities in Texas are hiring for Model Context Protocol jobs?

Cities in Texas with the most Model Context Protocol job openings:

Infographic showing various Model Context Protocol job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Agentic AI Lead - W2 only

Dallas, TX • On-site

Kasmo Inc.
IT Services • 201 - 500 employees

Other

Posted 4 days ago


Job description

Title: Agentic AI Lead

Location: Dallas, TX / San Jose, CA

Employment Type: Contract to hire

Experience: 10 years to 15 years

Role Overview

We are seeking an Agentic AI Lead to design, build, and deploy autonomous AI systems. In this role, you will move beyond basic prompt engineering to create self-reasoning agents that execute complex workflows. You will integrate these agents into our Microservices Architecture and leverage the Model Context Protocol (MCP) to connect LLMs seamlessly with enterprise data sources, development environments, and secure APIs.

Key Responsibilities

l   Translate Needs: Convert ambiguous client business problems into highly technical product specifications for engineering activities.

l   Manage Expectations: Communicate limitations transparently while proposing viable alternative architectures

l   Agent Architecture: Design and deploy multi-agent systems capable of autonomous planning, reasoning, reflection, and task execution

l   MCP Tooling Development: Build and maintain Model Context Protocol (MCP) servers and clients to securely expose data, file systems, and enterprise tools to LLMs.

l   Microservices Integration: Wrap AI agents, RAG engines, and vector stores into modular, scalable microservices using Docker and Kubernetes.

l   Tool & API Orchestration: Implement advanced tool-calling architectures to connect LLMs to production databases, external APIs, and internal software systems

l   Pipeline Optimization: Evaluate and optimize agentic workflows for token efficiency, latency, context-window usage, and decision-making accuracy.

Required Skills & Qualifications

l   Programming: Expert proficiency in Python or TypeScript.

l   AI Orchestration: Hands-on experience with LangGraph, CrewAI, AutoGen, or LangChain.

l   Model Context Protocol: Practical experience implementing or consuming open-source and custom MCP tools/servers.

l   Architecture: Deep understanding of distributed systems, REST/gRPC APIs, message brokers (Kafka/RabbitMQ), and microservice communication.

l   Cloud & DevOps: Strong experience with containerization (Docker) and deploying services to cloud infrastructure (AWS, Google Cloud Platform, or Azure).

l   AI Expertise: Experience on vector databases embeddings, semantic search, and RAG pipelines