We’re looking for a Software Architect who wants to do more than design systems on a whiteboard. This is a hands-on role for someone who enjoys setting technical direction and writing the code that brings that direction to life.
You’ll own the architecture of enterprise applications, including how services are designed, how data flows, how systems integrate, and how applications scale securely and reliably. You’ll also help shape how AI becomes part of our products, building solutions that combine traditional software architecture with LLM-powered capabilities and intelligent agents.
This role is ideal for an experienced architect, technical lead, or senior engineer who still loves to build and wants meaningful influence over both architecture and execution.
What You'll Do
- Own application architecture across services, APIs, identity, data access, and integrations.
- Write production code regularly across back-end services, APIs, and front-end applications.
- Build new services and features from initial design through deployment and production support.
- Design scalable, reliable, secure, and multi-tenant applications.
- Create prototypes and proofs of concept, then turn the strongest ideas into production-ready solutions.
- Help modernize legacy applications toward cloud-native architectures while maintaining ongoing product delivery.
- Develop AI-powered capabilities using LLMs, retrieval-augmented generation (RAG), tool calling, and agents.
- Design APIs and application capabilities that can be securely used by AI agents, including through protocols such as MCP.
- Implement evaluation, guardrails, and cost monitoring to ensure AI features are reliable, safe, and sustainable in production.
- Help determine where AI adds meaningful value and where traditional software solutions are the better approach.
- Review code, pair with engineers, and help solve complex technical problems.
- Establish strong engineering practices around automated testing, observability, security, performance, and resilience.
- Use modern AI-assisted development tools to improve engineering productivity and quality.
- Create architecture decision records and reference implementations that engineering teams can put into practice.
- Partner closely with Product, UX, QA, Security, and DevOps to turn business goals into scalable technical solutions.
Design and Build
Build AI into the Product
Raise the Engineering Bar
What We're Looking For
- 8+ years of software development experience, including 2+ years in an architect, technical lead, or senior engineering role with ownership of system design.
- Strong hands-on development skills and recent experience contributing production code.
- Experience designing and operating multi-tenant SaaS or enterprise applications.
- Experience building AI-powered features using LLMs, ideally including RAG, agents, tool/function calling, or structured outputs.
- Deep expertise in at least one modern development language such as C#/.NET, Java, TypeScript, or Python, with working knowledge of another.
- Experience with modern front-end frameworks such as React or Angular.Strong knowledge of microservices, event-driven architecture, domain-driven design, and API design.
- Experience with Azure or AWS, containers, Kubernetes, and/or serverless architectures.
- Knowledge of SQL and NoSQL data design, messaging platforms such as Kafka or Service Bus, and caching strategies.
- Understanding of modern identity and application security, including OAuth 2.0/OIDC, RBAC, OWASP practices, and secure handling of data used with AI models.
- Experience with CI/CD, infrastructure as code, observability, automated testing, and performance optimization.
How You Work
You’re an architect who likes to stay close to the technology. You can move from an architecture discussion to a pull request, explain complex technical trade-offs to both engineers and business partners, and help teams turn good ideas into working software.
You’re also comfortable using AI development tools such as GitHub Copilot, Claude Code, Cursor, or similar tools as part of your everyday engineering workflow, while knowing when AI is useful and when a simpler deterministic solution is the better choice.
Nice to Have
- Experience with multi-agent orchestration or AI evaluation pipelines.
- Experience with fine-tuning or open-weight/smaller language models.
- Experience modernizing legacy or acquired products into a more unified platform.
- Experience working in PCI DSS, SOC 2, or GDPR environments.
- Background in retail, payments, loyalty, or supply chain software.
- Relevant certifications such as Azure Solutions Architect, Azure AI Engineer, or AWS Solutions Architect.