Chief Agentic Systems Architect

Our client is looking for a Chief Agentic Systems Architect to transform a 10+ year legacy codebase into a highvelocity, agentoperable architecture.

This role sits at the intersection of software architecture, AIagent orchestration, and engineering governance. You will design system patterns, MCP interfaces, and cognitive context layers that allow LLMs and autonomous agents to safely refactor, test, and ship production code with minimal human intervention.

Responsibilities:
Decompose legacy monoliths into agentreadable, modular systems with strict boundaries and single responsibility
Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contractdriven interfaces
Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AIdriven engineering workflows
Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AIconsumable tools
Own contractfirst API design as the primary interface between human intent and autonomous agent execution
Act as architectural gatekeeper for AIgenerated pull requests, ensuring scalability, security, and longterm maintainability
Mandate testdriven development (TDD) and characterization testing to preserve legacy behavior during refactoring
Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity

Requirements:
15+ years in software architecture, platform engineering, or technical leadership
Deep handson expertise with TypeScript, .NET, and Node.js
Proven experience modernizing large, undocumented legacy systems
Strong background in API design, distributed systems, and modular architectures
Practical experience with agentic development, MCP, LLM tooling, or AIassisted engineering
Bias toward clean code, deterministic systems, and productiongrade AI
Availability to work until 2 pm – 3pm US EST

Will be a plus:
Experience with remotefirst or globally distributed teams
Background in SaaS transformations, scaleups, or PEbacked environments
Comfort operating in highambiguity, highownership settings

Why this role matters:
You are not adding AI features.
You are designing the architectural substrate that allows AI to safely build software at scale.
This is a careerdefining role for architects shaping how autonomous systems write, change, and govern production code.