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Transform legacy monoliths into modular, agent-operable architectures using modern design patterns and contract-driven interfaces. Act as an architectural gatekeeper for AI-generated code while ensuring system scalability, security, and maintainability.
Want to design the architecture that lets AI agents safely refactor, test and ship production code? Then let's talk.
Our client acquires enterprise software companies and turns them into AI-native, profitable, scalable businesses. They are a remote-first, AI-forward team spread across the globe, offering high ownership, flexibility and impact, work across multiple products and technologies, and growth pathways across engineering, product and leadership.
The job: transform a 10+ year legacy codebase into a high-velocity, agent-operable architecture, at the intersection of software architecture, AI-agent orchestration and engineering governance.
Contract Type: Contract, full-time
Location: Fully remote from Eastern Europe, working US morning hours (Scrum).
What you'll do
Agent-operable system architecture
Decompose legacy monoliths into agent-readable, modular systems with strict boundaries and single responsibility
Lead incremental modernization using the Strangler Pattern, wrapping legacy logic in modern, contract-driven interfaces
Enforce SOLID principles, Dependency Injection, and Hexagonal Architecture to ensure deterministic AI execution and low regression risk
Agentic framework & MCP leadership
Architect and maintain the agent context layer: standardized Skills, Rules, and Commands for AI-driven engineering workflows
Build and operate Model Context Protocol (MCP) servers exposing legacy APIs, services, and databases as typed, secure, AI-consumable tools
Own contract-first API design as the primary interface between human intent and autonomous agent execution
Engineering governance & AI quality control
Act as architectural gatekeeper for AI-generated pull requests, ensuring scalability, security, and long-term maintainability
Mandate test-driven development (TDD) and characterization testing to preserve legacy behavior during refactoring
Monitor and optimize agentic reasoning loops to balance cost, speed, and architectural integrity
What we're looking for
4+ years in software architecture, platform engineering, or technical leadership
Proven experience modernizing large, undocumented legacy systems
Deep hands-on expertise with TypeScript, .NET, and Node.js
Strong background in API design, distributed systems, and modular architectures
Practical experience with agentic development, MCP, LLM tooling, or AI-assisted engineering
Bias toward clean code, deterministic systems, and production-grade AI
Nice to have
Experience with remote-first or globally distributed teams
Background in SaaS transformations, scale-ups, or PE-backed environments
Comfort operating in high-ambiguity, high-ownership settings
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