Agentic AI & MCP Architect

Agentic AI & MCP Architect

The Agentic AI & MCP Specialist will architect, develop, and operationalize next-generation agentic systems powered by advanced LLMs and Model Context Protocol (MCP) frameworks. This role focuses on building intelligent, multi-step, tool-using agents that can autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem. This position requires a deeply skilled software developer who combines strong engineering fundamentals with hands-on experience creating agentic systems, working with MCP-based integrations, designing LLM-driven tools, and building secure, scalable AI applications.

This position requires that all candidates are eligible to obtain & maintain a Public Trust clearance.

Key Responsibilities

• Design and implement agent orchestration frameworks.
• Integrate model-driven decision logic and build robust, production-grade agent capabilities.
• Provide technical leadership and explore cutting-edge agentic patterns.
• Drive proof-of-concept innovation.
• Partner with engineering and product teams to translate experimental architectures into real-world impact.

Required Qualifications

Education:

A Bachelor's degree in computer science, software engineering, or a relevant field is required.

Experience:

10+ years of experience is required. Ability to obtain & maintain a Public Trust clearance.

Technical

Skills:

• Strong software engineering background with experience building production-grade applications and services.
• Expertise developing agentic AI systems, including planning, tool-use, multi-step reasoning, or autonomous decisioning logic.
• Hands-on experience designing and implementing MCP-based integrations, tool interfaces, or model-driven service frameworks.
• Ability to translate business requirements into scalable AI-driven solutions.
• Proficiency with LLM development practices including fine-tuning, RAG integration, and prompt engineering.
• Strong Python development skills and familiarity with distributed compute environments, APIs, and microservices.
• Experience integrating agents or LLM-driven components into cloud platforms (Azure, AWS, GCP).
• Understanding of LLMOps/MLOps principles including versioning, testing, deployment automation, and monitoring.
• Demonstrated ability to lead solution design and mentor developers.
• Experience with version control and modern CI/CD practices (e.g., Git/Git Hub).

Preferred Qualifications

• Experience building multi-agent systems or agent swarms.
• Familiarity with advanced tool-calling strategies, including dynamic tool selection or function-call planning.
• Experience with structured LLM evaluation methods or agent benchmarking.
• Knowledge of performance optimization techniques for LLMs and agents.
• Background integrating agentic components with large-scale data platforms (e.g., Databricks, Snowflake, Spark).
• Hands-on experience developing innovative POCs in R&D environments.
• Familiarity with emerging agentic frameworks such as Strands Agents, Lang Graph, or CrewAI.
• Exposure to safety-oriented design patterns for autonomous systems.
• Experience designing and building secure, compliance-aware systems that handle sensitive data in accordance with HIPAA and federal security standards.
• Active or Prior Public Trust level clearance or higher.