Own end-to-end solution architecture for .NET-based platforms and products
define target-state architectures, reference patterns, and technical roadmaps aligned to business goals.
Design scalable, secure, maintainable systems using appropriate architecture patterns (e.g., modular monolith/microservices, event-driven, domain-oriented design) and enforce sound engineering principles.
Lead cloud architecture and engineering alignment (e.g., Azure/AWS/GCP): resiliency, identity/access, security-by-design, observability, and cost-aware architectures.
Drive legacy modernization
assess current-state platforms, propose migration approaches, reduce technical debt, and ensure smooth transitions with minimal business disruption.
Define integration strategy across internal and external systems (APIs, messaging, data flows), ensuring reliability, performance, and interoperability.
Establish architecture governance
standards, reusable components, quality gates, automation, and best practices that improve delivery consistency and maintainability.
Lead AI adoption and enablement
identify high-value use cases, embed AI capabilities into products, and implement responsible/secure AI practices and guardrails enterprise-wide
Make high-impact technical decisions, align engineering efforts with business goals, and drive the evolution of both software architecture and AI strategy

Proven experience in solution/software architecture with a strong track record of making high-impact technical decisions and guiding teams across domains.
Deep expertise in the .NET ecosystem (C#, modern .NET/.NET Core), including designing reliable, reusable, maintainable codebases and applying architecture patterns effectively.
Strong distributed systems background
scalability, performance optimization, concurrency, reliability, and operational excellence (monitoring, incident learnings, resilience).
Hands-on cloud experience (Azure/AWS/GCP) with modern engineering practices (CI/CD, containers, IaC, DevSecOps collaboration).
Integration and data experience
API design (REST/gRPC), eventing/messaging, and working knowledge of relational and non-relational storage and data flows.
AI/GenAI adoption experience
building or integrating AI features (LLMs/GenAI), understanding Responsible AI principles, AI security, and governance best practices.
Strong communication and leadership skills
translate business needs into technical direction, mentor engineering teams, and influence stakeholders across product, delivery, and client organizations.

Solution Development Architect

Key skills