Agentic AI Architect & MCP Systems Lead

Socket.dev

United States

On-site

USD 135,000 - 216,000

Full time

5 days ago
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Job summary

Peraton is seeking an experienced Specialist to architect and implement agentic AI systems powered by LLMs and MCP frameworks. You will build multi-step, tool-using agents that autonomously reason, plan, and execute complex workflows across cloud-based analytics.

The role focuses on production-grade agent capabilities, safe AI techniques, and collaboration with engineering/product teams. You will lead design efforts, mentor developers, and translate experimental architectures into real-world

Qualifications

  • Strong software engineering background with production-grade apps/services.
  • Expertise building agentic AI systems with planning, tool-use, multi-step reasoning.
  • Hands-on MCP-based integrations, tool interfaces, or model-driven service frameworks.
  • Translate ambiguous requirements into scalable AI-driven solutions.

Responsibilities

  • Architect, develop, and operationalize agentic systems powered by LLMs and MCP.
  • Design and implement agent orchestration frameworks and model-driven logic.
  • Lead integration of agents/LLM components into cloud platforms and data ecosystems.
  • Mentor developers and communicate complex AI architectures to stakeholders.

Skills

Agentic AI
Python
LLM integration
Cloud platforms
MCP integrations
Software engineering
Git/GitHub
CI/CD
Leadership
AI governance

Education

BS/BA
MS/MA
PhD

Tools

Azure
AWS
GCP
Databricks
Snowflake
Spark

Job description

Peraton is seeking an experienced Specialist to architect and implement agentic AI systems powered by LLMs and MCP frameworks. You will build multi-step, tool-using agents that autonomously reason, plan, and execute complex workflows across cloud-based analytics.

The role focuses on production-grade agent capabilities, safe AI techniques, and collaboration with engineering/product teams. You will lead design efforts, mentor developers, and translate experimental architectures into real-world

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