Note: The job is a remote job and is open to candidates in USA. Dice is seeking a Backend Architect for their AI-Enabled Platform Engineering team. The role involves architecting and delivering scalable backend systems and APIs while leveraging AI technologies to enhance engineering productivity and system design.
Responsibilities
- Architect and build scalable backend systems and microservices that power workflow-driven, AI-enabled application experiences
- Design and implement API-first architectures (REST/GraphQL/event-driven) supporting modular, extensible platform capabilities
- Build systems enabling collaboration workflows, evaluation pipelines, and artifact generation/storage
- Develop a centralized system of record for structured data and domain-specific workflows
- Integrate backend services with enterprise systems, analytics platforms, and data pipelines
- Enable AI-driven workflows by designing backend orchestration layers that interact with structured and unstructured data sources
- Design and implement scalable, cloud-native backend architectures leveraging Azure services—including Azure Kubernetes Service (AKS), Azure Functions, Azure Service Bus, and Azure App Services—to build resilient, event-driven, and high-performance application platforms
- Implement security, governance, and compliance controls, including safeguards for restricted attributes and enterprise policy alignment
- Design and build systems for handling uploaded artifacts, external datasets, and document processing pipelines
- Leverage Claude AI extensively for backend engineering acceleration, debugging, system design, and documentation
- Establish and scale AI-assisted backend engineering practices to improve development, velocity and quality
- Own backend architecture decisions, ensuring scalability, resiliency, performance, and maintainability
- Operate as a deeply hands-on IC, contributing to coding, design reviews, and engineering execution
- Ensure strong engineering standards including testing, observability, reliability, and production readiness
Skills
- 15+ years of software engineering experience, including 5+ years at Architect / Principal IC level
- Proven experience designing and delivering large-scale backend and distributed systems
- Demonstrated ownership of architecture and delivery for enterprise-grade backend platforms
- Strong experience in embedded/forward-deployed engineering models collaborating with product teams
- Active hands-on backend engineer working on production-grade systems
- Extensive usage of Claude AI or equivalent AI coding assistants to accelerate backend development
- Deep expertise in backend development using Python, Java, or .NET (C#)
- Strong experience building microservices-based architectures and distributed systems
- Strong experience designing and implementing backend systems using Azure-native services, including Azure Cosmos DB for distributed data management, Azure messaging services (Service Bus/Event Grid) for event-driven architectures, and Azure Active Directory (Azure AD) for secure identity and access management
- Expertise in API-driven architectures (REST, GraphQL, event-driven systems)
- Strong knowledge of data modeling, persistence, and database systems (SQL/NoSQL)
- Experience with event-driven systems, messaging queues, and asynchronous processing
- Strong understanding of scalability, caching, performance optimization, and resiliency patterns
- Experience implementing authentication, authorization, and enterprise-grade security controls
- Proven ability to design end-to-end backend workflows spanning APIs, business logic, and data layers
- Hands-on experience with cloud-native application development backend services, and API management
- Experience integrating with enterprise systems, data pipelines, and analytics platforms
- Familiarity with designing systems that support AI-assisted workflows and intelligent application experiences
- Strong understanding of CI/CD pipelines, observability, deployment models, and performance monitoring in distributed systems
- Extensive hands-on usage of Claude AI for software development, including: Code generation and rapid prototyping, Debugging and optimization, System design exploration, Documentation and knowledge capture
- Demonstrated ability to accelerate GTM timelines using Claude AI, reducing development cycle times while maintaining high quality
- Experience establishing Claude-driven development workflows and best practices within engineering teams
- Ability to balance AI-assisted development with strong engineering judgment, ensuring maintainable, production-grade code
- Strong grounding in engineering best practices: code quality, modular architecture, testing discipline, and maintainability
- Excellent problem-solving and system design skills, with the ability to operate independently in high-ownership IC roles
- Strong communication skills, including working with product managers and stakeholders to shape technical solutions
- Certifications such as Azure / AWS / Google Cloud Platform Architect certifications
- Experience building AI-enabled backend platforms with complex workflows and integrations
- Demonstrated use of AI coding assistants to improve backend engineering productivity
- Exposure to enterprise SaaS platforms, workflow systems, or data-driven applications
- Experience working in high-velocity, embedded delivery environments
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