Senior MCP (Model Context Protocol) Developer / AI Agent Engineer

Experience

5+ years of software development experience

2+ years of hands-on experience building AI/LLM-based applications or Agentic AI solutions in enterprise environments

Job Summary

We are looking for an experienced Senior MCP (Model Context Protocol) Developer to design, develop, and deploy enterprise-grade MCP servers and AI agents on the Google Cloud ecosystem. The ideal candidate should have strong expertise in Google Vertex AI Agent Engine, Agent Development Kit (ADK), Gemini, OAuth 2.0, Cloud Run, and Python, with a deep understanding of how AI agents securely discover and consume MCP services.

The role involves building secure, scalable, production-ready MCP infrastructure while ensuring enterprise-grade authentication, governance, monitoring, and operational excellence.

Key Responsibilities

Design, develop, and deploy MCP (Model Context Protocol) servers using FastMCP or enterprise integration platforms such as Workato.

Build and manage the complete MCP consumption lifecycle, including:

JSON-RPC communication

Streamable HTTP

Tool discovery

Session handshake

Agent connectivity

Develop and deploy AI agents using Google Vertex AI Agent Engine and Agent Development Kit (ADK).

Integrate agents with Gemini Enterprise and publish/register them for enterprise testing and consumption.

Implement secure OAuth 2.0 Authorization Code Flow with PKCE, refresh tokens, offline access, and per-user token forwarding.

Ensure every agent request executes under the authenticated user's permissions.

Design secure authentication and authorization mechanisms using IAM, service accounts,



and Secret Manager.

Build reliable, scalable, and maintainable production-grade AI services.

Monitor, troubleshoot, and optimize MCP servers, AI agents, authentication flows, and runtime behavior.

Implement enterprise governance and security best practices including:

Least privilege access

Secure secret management

Private networking

Token protection

Fail-safe architecture

Collaborate with AI architects, cloud engineers, security teams, and business stakeholders to deliver enterprise AI solutions.

Required Technical Skills

AI & Agent Frameworks

Strong understanding of Model Context Protocol (MCP)

Experience building and consuming MCP servers

MCP protocol fundamentals

JSON-RPC

Streamable HTTP

Tool Discovery

Session Handshake

Agent orchestration

Google Cloud & Vertex AI

Google Cloud Platform (GCP)

Vertex AI

Vertex AI Agent Engine

Agent Development Kit (ADK)

Gemini Models

Cloud Run

IAM

Service Accounts

Secret Manager

Authentication & Security

OAuth 2.0

OpenID Connect (OIDC)

Authorization Code Flow

PKCE

Refresh Tokens

Access Token Management

Per-user Token Forwarding

Identity Federation

Enterprise Authentication

Programming

Python (preferred)

Experience developing cloud-native AI applications

REST APIs





Microservices architecture

DevOps & Cloud

CI/CD pipelines

Containerization

Docker

Cloud deployment

Logging & Monitoring

Production troubleshooting

Enterprise Engineering

Secure software development

Scalability

Reliability

Observability

Governance

Performance optimization

Mandatory Skills

5+ years of software engineering experience.

2+ years of enterprise AI/LLM/Agent development experience.

Strong hands-on experience with Google Vertex AI Agent Engine.

Experience with Agent Development Kit (ADK).

Strong knowledge of Gemini Models.

Experience building and consuming MCP servers.

Deep understanding of Model Context Protocol.

Strong knowledge of OAuth 2.0, OIDC, PKCE, refresh tokens, and enterprise authentication.

Experience with Cloud Run, IAM, Secret Manager, and service accounts.

Solid Python programming skills.

Experience delivering production-grade enterprise AI applications.

Nice to Have

Experience registering MCP servers and AI agents with Gemini Enterprise or enterprise Agent Registries.

Experience with Workato or other iPaaS platforms.

Advanced prompt engineering for AI agents.

Experience building enterprise internal AI platforms and developer tooling.

Knowledge of enterprise governance for Agentic AI.

Experience with multi-agent architectures.

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Google Cloud certifications are a plus.

Experience working in enterprise-scale cloud environments.

Excellent communication and stakeholder management skills.

📌 Senior MCP (Model Context Protocol) Developer / AI Agent Engineer (Hyderabad)
🏢 CriticalRiver
📍 Hyderabad