Systems Architect (AI & Cloud) - Remote

CentralSquare Technologies

2d•Remote

About The Position

At CentralSquare, we don’t just build software - we power public servants and uplift communities with Hero-Grade Technology. Every line of code, every feature we deliver helps heroes across North America protect, serve, and save lives. When you join us, you become part of a mission-driven team creating technology that makes communities safer and stronger. Your Growth Matters. We believe heroes deserve opportunities to rise. That’s why we invest in your career with mentorship, learning programs, and clear paths for advancement. If you’re motivated, there’s no limit to how far you can go. Your Commitment Deserves Reward. We offer competitive compensation and a benefits package designed to support your life inside and outside of work—tuition reimbursement, parental leave, paid volunteer hours, and unlimited PTO. Plus, our flexible work environment gives you the freedom to balance your heroic work with personal well-being, whether you’re in the office or remote. Join us and help build the tools that power real-life heroes. Together, we make a difference. We are looking for a Senior Architect who will define and drive how AI builds software across our platform — not just writing code with AI assistance, but designing the orchestration layers, agent pipelines, and spec-driven workflows that allow AI to produce production-quality output at scale. This is an architecture role where your technical depth in C#/.NET and cloud-native systems meets a hands-on obsession with AI-first engineering practices. You will serve as a technical leader and architect across multiple product teams, driving cloud-native modernization of multiple products. We need architects who can own the technical vision for that system and elevate every team’s ability to execute against it.

Requirements

technical depth in C#/.NET
cloud-native systems
hands-on obsession with AI-first engineering practices

Responsibilities

Define and own the cloud-native architecture for C# services, APIs, and containerized workloads running on AWS EKS, including service decomposition, data access patterns, and cross-cutting concerns.
Lead monolith decomposition strategy — identifying bounded contexts, defining service boundaries, and creating incremental extraction plans that let teams carve out services from legacy systems without big-bang rewrites.
Architect the migration from legacy ASP.NET WebForms (.aspx) or other legacy UI systems to modern SPA frameworks (Angular or equivalent), defining the incremental migration path, component architecture, state management patterns, and coexistence strategy that lets teams move page by page without a full rewrite.
Drive OIDC modernization across products — migrating from legacy or inconsistent authentication patterns to standards-based OIDC flows
Architect event-driven and event-sourced systems, designing domain event contracts, message schemas, and replay/projection patterns that support offline capability, audit trails, and eventual consistency across distributed services.
Design and implement GraphQL APIs as a unified query layer across decomposed services, including schema federation, resolver architecture, and performance considerations like query complexity limits and dataloader patterns.
Design and evolve AI orchestration pipelines — multi-agent architectures, sub-agent delegation, spec-to-code-to-test workflows — that serve as the primary mechanism for code production across teams.
Prepare products for AI integration by designing MCP-ready architectures — exposing product capabilities as well-defined tool interfaces, structured context providers, and machine-consumable APIs that allow AI agents and third-party integrations to interact with our platform programmatically.
Establish the specification framework that feeds AI-driven development: what a spec must contain, how it maps to architecture context, data contracts, and behavioral validation, so that AI output is predictable and production-grade.
Drive legacy system refactoring strategy, making pragmatic decisions about what to rewrite, what to wrap, and what to strangle — balancing technical debt reduction against delivery velocity and risk.
Architect for resilience and scalability — circuit breakers, retry policies, graceful degradation, horizontal scaling patterns, backpressure handling, and health check architectures that keep systems stable under load and failure.
Define and enforce observability architecture — distributed tracing, structured logging, metrics, and DAU telemetry — as a first-class system concern, not an afterthought.
Integrate AI tooling (Claude, Copilot, custom agents) into development workflows, continuously raising the ceiling on what automated pipelines can reliably deliver.