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Model Context Protocol Jobs (NOW HIRING)

SolGenie

AI Engineer

Manhattan, NY · On-site

Design and implement Model Context Protocol (MCP)-based integrations so AI assistants and agents can securely discover and connect to internal systems, databases, and services through standardized ...

Koitecc Solutions

$106 - $149/hr

The engineer applies hands‑on experience with large language models and Model Context Protocol (MCP) capabilities to support AI governance, secure AI integrations, and agentic security tooling.

New

FastTek

Senior Cloud Database Engineer

Dearborn, MI · On-site

$97K - $132K/yr

Define patterns for integrating Model Context Protocol (MCP) with databases for contextual AI interactions. * Intelligent Automation: Identify and implement AI-driven automation across the lifecycle ...

Empower

Security Automation Engineer

Overland Park, KS · On-site

The engineer applies hands-on experience with large language models and Model Context Protocol (MCP) capabilities to support AI governance, secure AI integrations, and agentic security tooling. What ...

Vings Technologies

Senior AI Agentic Engineer

Hoboken, NJ · On-site

$134K - $176K/yr

... · Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use · Define human-in-the-loop checkpoints, autonomy boundaries, and rollback ...

New

Instabase

Technical Lead Manager

San Francisco, CA · On-site

$23K - $270K/mo

Model Context Protocol (MCP) tool schemas and APIs. About You * 8+ Years of Professional Engineering Experience: A strong, proven background in software engineering, with significant tenure building ...

Remotestar

NY · On-site

$120 - $150/hr

Hands‑on experience building with Model Context Protocol (MCP) * Demonstrated use of Claude Code, GitHub Copilot, or similar AI development tools in production work * Experience implementing AI in ...

RIT Solutions, Inc.

LEAD AI Engineer

$104K - $138K/yr

... Model Context Protocol (MCP). • Good working experience developing and integrating AI solutions using AWS Bedrock, including prompt engineering, RAG, and enterprise application integration. • ...

ARK Infotech Spectrum

Principal Engineer

Irving, TX · On-site

The ideal candidate will be a seasoned engineering and platform architect with experience integrating Al coding assistants, autonomous software engineering agents, Model Context Protocol (MCP ...

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Model Context Protocol information

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$10

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How much do model context protocol jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for model context protocol in the United States is $31.37, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $39.18 per hour, depending on experience, location, and employer.

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.

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Model Context Protocol jobs near you
Infographic showing various Model Context Protocol job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $65,246 per year, or $31.4 per hour.

Lead Gen AI/Data Science Engineer ( with Model Training Experience)

TekPioneers - A TekGence Company

Jersey City, NJ • On-site

$112K - $147K/yr

Full-time

Posted 22 days ago

Job description

Lead AI Engineer with strong software engineering foundations and hands-on experience in Generative and Agentic AI.

•            Architect and Design production-ready applications leveraging Generative AI and agentic AI frameworks.
•            Build, Deploy and Monitor intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines.
•            Integrate new AI applications with traditional pre-existing applications.
•            Implement prompt engineering strategies, retrieval-augmented generation (RAG), and contextual memory systems.
•            Implement various AI coding techniques (context-driven, spec-driven development etc.).
•            Architect and implement AI agents capable of reasoning, planning, and multi-step task execution.
•            Implement and utilize Model Context Protocol (MCP) patterns to enable structured communication between agents, tools, and systems.
•            Provide mentoring and technical guidance to developers and other AI Engineers.
•            Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems.
•            Optimize latency, cost efficiency, and scalability of AI-powered workflows.
•            Collaborate with product managers, data teams, and software engineers to deliver AI features.
•            Ensure reliability through testing, logging, monitoring, and observability of AI behavior.
•            Own architectural decisions, coding standards, and best practices.
•            Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches.
•            Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows.
•            Support implementation of governance controls related to data handling, model behavior monitoring, and risk mitigation.
•            Research emerging AI tools and frameworks to continuously improve system capabilities.
•            Document AI workflows and maintain reproducible engineering processes.