Senior Software Architect (AI-Driven Development)

Senior Software Architect (AI-Driven Development)

100 % Remote

Top Skills’ Details

1. 10+ years of professional software development experience with C# and the .NET ecosystem, with at least 3 years operating in an architect position across multiple teams or products.

2. Proven experience decomposing monolithic applications into distributed, cloud-native services — you have defined bounded contexts, drawn service boundaries, and shipped incremental extractions in production environments.

3. Deep experience with SQL databases such as PostgreSQL, including data modeling for distributed systems, query optimization at enterprise scale, and designing data ownership boundaries during service decomposition

4. Strong AWS cloud architecture experience — you have designed and deployed production systems on AWS, making architectural decisions across compute, networking, storage, data, security, and cost management. You understand how to architect holistically on the platform.

5. Understanding of AI integration patterns and protocol-level interfaces like MCP or equivalent experience making products programmable and accessible to external AI agents.

When sending candidates, please include how their experience relates to the top skills. Please send their rate and salary ask.

Secondary Skills - Nice to Haves

• PostgreSQL
• Angular
• OpenTelemetry
• MCP
• Terraform

Job Description

Client is looking Senior Architects who will define and drive how AI builds software across their 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.

What You’ll Do

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 degrada…