Senior Software Architect (AI-Driven Development) - Remote

CentralSquare Technologies

1d•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.

Requirements

Technical depth in C#/.NET
Experience with cloud-native systems
Obsession with AI-first engineering practices
Experience as a technical leader and architect across multiple product teams
Experience driving cloud-native modernization of multiple products
Experience owning the technical vision for a system
Experience with AWS EKS
Experience with service decomposition
Experience with data access patterns
Experience with cross-cutting concerns
Experience with monolith decomposition strategy
Experience identifying bounded contexts
Experience defining service boundaries
Experience creating incremental extraction plans
Experience migrating from legacy ASP.NET WebForms (.aspx) or other legacy UI systems to modern SPA frameworks (Angular or equivalent)
Experience defining incremental migration paths
Experience defining component architecture
Experience defining state management patterns
Experience defining coexistence strategies
Experience driving OIDC modernization
Experience migrating from legacy or inconsistent authentication patterns to standards-based OIDC flows
Experience architecting event-driven and event-sourced systems
Experience designing domain event contracts
Experience designing message schemas
Experience designing replay/projection patterns
Experience designing and implementing GraphQL APIs
Experience with schema federation
Experience with resolver architecture
Experience with performance considerations like query complexity limits and dataloader patterns
Experience designing and evolving AI orchestration pipelines
Experience with multi-agent architectures
Experience with sub-agent delegation
Experience with spec-to-code-to-test workflows
Experience preparing products for AI integration
Experience designing MCP-ready architectures
Experience exposing product capabilities as well-defined tool interfaces
Experience exposing structured context providers
Experience exposing machine-consumable APIs
Experience establishing specification frameworks for AI-driven development
Experience driving legacy system refactoring strategy
Experience architecting for resilience and scalability
Experience with circuit breakers
Experience with retry policies
Experience with graceful degradation
Experience with horizontal scaling patterns
Experience with backpressure handling
Experience with health check architectures
Experience defining and enforcing observability architecture
Experience with distributed tracing
Experience with structured logging
Experience with metrics
Experience with DAU telemetry
Experience integrating AI tooling (Claude, Copilot, custom agents) into development workflows
Experience authoring ADRs, architecture decision records, and technical specifications
Experience mentoring and supporting engineers on AI-first development practices
Experience mentoring and supporting engineers on prompt engineering
Experience mentoring and supporting engineers on spec quality
Experience mentoring and supporting engineers on architectural patterns

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.
Author ADRs, architecture decision records, and technical specifications that serve as both human documentation and AI-consumable context.
Mentor and support engineers across multiple teams on AI-first development practices, prompt engineering, spec quality, and architectural patterns — acting as the connective tissue that keeps teams aligned on standards while moving fast independently.