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Model Context Protocol Jobs (NOW HIRING)

Whiztek Corp

Google Cloud Platform Engineer

Schaumburg, IL · On-site

$55 - $73.50/hr

Integrate and configure Model Context Protocol (MCP) servers both Google-provided (e.g., Workspace MCP) and custom/third-party as external agent tools * Stand up and manage multi-agent orchestration ...

ClifyX

Senior Agentic AI Builder

San Jose, CA · On-site

$107K - $136K/yr

... Model Context Protocol) - Practical experience with MCP client/server patterns for structured tool-to-data communication Qualifications : Required : • Agentic AI implementation experience in ...

TekCommands Inc

Senior AI Engineers

Hoboken, NJ · On-site

$114K - $157K/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 strategies ...

Upbound

AI Cybersecurity Engineer

Plano, TX · Hybrid

Agentic Systems and Model Context Protocol (MCP) Security * Apply Zero Trust principles to AI agents, ensuring agents operate under strict least-privilege policies with scoped, time-limited ...

Upbound

AI Cybersecurity Engineer

Plano, TX · Hybrid

Agentic Systems and Model Context Protocol (MCP) Security * Apply Zero Trust principles to AI agents, ensuring agents operate under strict least-privilege policies with scoped, time-limited ...

Xcede

Lead AI Engineer (San Francisco)

San Francisco, CA · On-site

$500K/yr

Build and maintain MCP (Model Context Protocol) servers and related infrastructure for agent communication, coordination, and enterprise service bus integration. * Accelerate code review processes by ...

RXinsider LTD.

AI Systems Engineer

Bolingbrook, IL · On-site

$130 - $150/hr

You'll work heavily with Model Context Protocol (MCP), LLM orchestration, APIs, tool calling, enterprise data, and asynchronous application architectures to turn individual AI models into capable ...

RXinsider LTD.

$130 - $150/hr

You'll work heavily with Model Context Protocol (MCP), LLM orchestration, APIs, tool calling, enterprise data, and asynchronous application architectures to turn individual AI models into capable ...

Upbound

AI Cybersecurity Engineer

Plano, TX · Hybrid

Agentic Systems and Model Context Protocol (MCP) Security * Apply Zero Trust principles to AI agents, ensuring agents operate under strict least-privilege policies with scoped, time-limited ...

Pyramid Consulting, Inc

AI/LLM Engineers

Denver, CO · On-site

RAG, MODEL CONTEXT PROTOCOL, LLMs, AWS SERVICES, ETL, SQL. • Hands-on experience building with LLMs -- prompt engineering, agent frameworks, tool-use patterns, or RAG systems. • Experience with ...

Saransh Inc

AI Architect - Remote

New York, NY · On-site

Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP). * Proven ability to architect and scale AI solutions for enterprise workloads (1M ...

CYNET SYSTEMS

Agentic AI Developer

San Jose, CA · On-site

$55 - $60/hr

Familiarity with Agent Development Kit (ADK), Model Context Protocol (MCP), and agent design in Vertex AI. * Strong understanding of cloud-native development on GCP. * Demonstrated ability to lead ...

Empower LLC

$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.

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Model Context Protocol information

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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.

Google Cloud Platform Engineer

Whiztek Corp

Schaumburg, IL • On-site

$55 - $73.50/hr

Other

Posted 6 days ago

Job description

We are looking for experienced Google Cloud engineers with hands-on expertise in Gemini Enterprise Agent Platform (GEAP), Google's managed platform for building, deploying, governing, and scaling enterprise-grade AI agents. This is a hands-on, build-and-deploy role: you will design agent architectures, stand up production hosting infrastructure, integrate Model Context Protocol (MCP) servers and tools, and ensure our agents are secure, observable, and cost-efficient at scale.
What You'll Do
  • Design, build, and deploy AI agents on GEAP using Google's Agent Development Kit (ADK) or equivalent frameworks, including both pro-code and low-code (Agent Studio) approaches
  • Deploy agents to GEAP's fully-managed Agent Runtime, configuring short-term Sessions and long-term Memory Bank integration
  • Integrate and configure Model Context Protocol (MCP) servers both Google-provided (e.g., Workspace MCP) and custom/third-party as external agent tools
  • Stand up and manage multi-agent orchestration patterns (e.g., orchestrator/sub-agent graphs, Agent Fabric-style fleets) where specialized agents handle discrete tasks and coordinate via defined protocols
  • Configure Agent Gateway policies, authorization, and Agent Identity for secure, auditable, and traceable agent actions
  • Define and provision the Google Cloud Platform infrastructure needed to host agents: networking (VPC, Private Service Connect, hybrid/on-prem connectivity), IAM, compute (GKE, Agent Platform Endpoints), and OAuth/credential flows for production agent authentication
  • Set up Agent Evaluation, Agent Observability, and Agent Optimizer to monitor drift, trace performance issues, and control compute/token costs in production
  • Advise stakeholders on exactly what's required licensing, APIs, IAM roles, network topology, compute sizing to host AI agents on GEAP, and translate that into clear deployment runbooks
  • Troubleshoot production issues across the agent stack, from model/tool calls to networking and platform-level governance controls
Required Experience
  • Demonstrated hands-on experience with GEAP (or its predecessor, Vertex AI Agent Builder/Vertex AI Pipelines) not just familiarity from documentation
  • Strong Google Cloud Platform fundamentals: IAM, VPC networking, GKE, Cloud Run or similar compute, Private Service Connect
  • Experience building or integrating MCP (Model Context Protocol) servers and tools
  • Experience with Google's Agent Development Kit (ADK) or comparable agent frameworks
  • Familiarity with agent orchestration concepts (multi-agent systems, task graphs, tool calling, sessions/memory)
  • Solid understanding of OAuth 2.0 flows and secure credential handling for production, server-side applications
  • Comfortable working with gcloud CLI, Google Cloud Console, and infrastructure-as-code tooling
Nice to Have
  • Experience with Google Workspace MCP servers and the Workspace Developer Preview Program
  • Background in ML/platform engineering or cloud architecture roles
  • Experience with third-party agent interoperability (e.g., Open Agent Network, Salesforce/ServiceNow agent integrations)
  • Google Cloud certifications (Professional Cloud Architect, Professional ML Engineer, etc.)
  • Experience with cost governance/optimization for high-volume agent workloads

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