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
7+ 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