Location: New York OR New Jersey – Remote (but travel when required)
Travel: 25% during active client engagements
Position – Backend Architect – AI-Enabled Platform Engineering (Hands-on IC)
Experience: 15+ years of software engineering experience, including 5+ years at Architect / Principal IC level
Location: New York OR New Jersey – Remote (but travel when required)
Travel: 25% during active client engagements
Role :- FTE
End Client: Service-based industry
Experience Level: 15+ years
Full Stack Architect – AI-Enabled Platform Engineering (Hands-on IC)
Product Development, Sustenance, Modernization & Agentic AI infusion
About the Role :
As a Backend Architect, you will be the senior-most hands-on backend engineer responsible for architecting and delivering scalable, secure, and high-performance backend systems powering a unified AI-enabled application platform.
You will lead the design and development of backend services, APIs, data systems, and integrations that enable workflow orchestration, collaboration, and intelligent decision-making capabilities across the platform.
The platform consolidates fragmented workflows into a centralized system of record, supporting modules such as scorecards, evaluations, collaboration workflows, and artifact management.
You will also drive deep integration with enterprise systems, data pipelines, analytics platforms, and external data artifacts, enabling seamless interaction across structured and unstructured data sources
You will leverage Claude AI extensively as an engineering productivity accelerator for backend development, enabling faster delivery, improved code quality, and efficient system design
This is a pure individual contributor architect role, with ~70–75% hands-on engineering across system design, backend development, API construction, and distributed systems implementation.
Key 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
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Required Qualifications
- 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
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Backend Engineering (Required — Primary Focus Area)
- 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 BEvent 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
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Cloud & Platform Engineering (Required — Primary Focus Area)
- 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.
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Claude AI–Driven Engineering (Required — Differentiator)
- 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.
Engineering Excellence & Delivery (Required)
- 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
Preferred Qualifications
• 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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