Full Stack Architect

Full Stack Architect – AI-Enabled Platform Engineering (Hands-on IC)

Product Development, Sustenance, Modernization & Agentic AI infusion

Travel: 25% during active client engagements

Experience Level: 15+ years

Key Responsibilities

• Architect and build the end-to-end full stack platform that unifies fragmented workflows into a centralized, scalable, and AI-enabled application experience.
• Design and implement frontend and backend components, including application shell, UI layers, APIs, and supporting services, ensuring performance, scalability, and production readiness.
• Develop and integrate workflow-driven modules such as collaboration interfaces, structured evaluation forms, and exportable artifacts for downstream usage and reuse.
• Build and manage integrations with enterprise systems, data pipelines, analytics platforms, and external data artifacts, enabling seamless interaction across structured and unstructured data sources.
• Design and implement systems that support AI-assisted workflows, enabling enriched user interactions, intelligent recommendations, and data-driven decision-making capabilities.
• Leverage Claude AI extensively as an engineering productivity accelerator—driving faster GTM through rapid prototyping, full stack development, debugging, and system design acceleration.
• Establish and scale Claude-driven development practices to enhance developer productivity, reduce delivery cycles, and improve code quality across the engineering lifecycle.
• Own full stack technical design and architecture, translating product and workflow requirements into robust, scalable, and maintainable implementations.
• Operate as a highly hands-on individual contributor, actively participating in coding, design reviews, and day-to-day engineering execution within an embedded team model.
• Ensure high engineering standards across the stack, including code quality, modular architecture, testing rigor, usability, and long-term maintainability.
• Drive execution discipline and delivery outcomes, ensuring the platform is production-grade, scalable, and aligned with rapid iteration needs enabled by AI-assisted development.

Required Qualifications

• 15+ years of software engineering experience, including 5+ years at Principal Architect / Senior IC level building large-scale full stack platforms in enterprise environments.
• Proven experience designing and delivering end-to-end full stack systems that combine rich user interfaces, scalable backend services, and data-driven workflows.
• Demonstrated ownership of architecture and delivery for multiple large-scale platform programs with measurable impact on scalability, performance, usability, and time-to-market.
• Active hands-on engineer, currently building production-grade applications across frontend and backend, reviewing PRs, and driving engineering standards.
• Strong experience working in embedded/forward-deployed engineering models, collaborating directly with product and stakeholders to translate evolving requirements into scalable systems.
• Extensive usage of Claude AI or equivalent AI coding assistants as a core development accelerator—demonstrated impact on engineering velocity, code quality, and GTM timelines.
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Full Stack Engineering (Required — Primary Focus Area)

• Strong expertise in frontend development using modern frameworks (React, Angular, or equivalent) for building scalable, responsive, and intuitive user interfaces.
• Deep expertise in backend development using Python, Java, or .NET (C#) for building high-performance, enterprise-grade systems.
• Hands-on experience building API-driven and service-oriented architectures (REST, GraphQL, event-driven patterns) across the stack.
• Proven ability to design and build scalable backend services and microservices architectures with strong modular and domain-driven design principles.
• Strong knowledge of data modeling, persistence layers, and database design (SQL/NoSQL) for high-volume, high-performance systems.
• Experience implementing event-driven and asynchronous systems using messaging, queues, and distributed processing patterns.
• Strong understanding of performance optimization, caching, scalability, and resiliency patterns across frontend and backend layers.
• Experience building secure applications with authentication, authorization, and governance controls for enterprise environments.
• Proven ability to design and deliver end-to-end application workflows spanning UI, 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, including frontend hosting, 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.
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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
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Preferred Qualifications

•      Certifications relevant to full stack and cloud engineering such as Azure Solutions Architect Expert, Azure Developer Associate, AWS / Google Cloud Platform equivalents, along with strong proficiency in Python, Java, or .NET (C#) ecosystems.

•      Demonstrated use of Claude AI (or equivalent AI coding assistants) to accelerate full stack development, driving measurable improvements in engineering productivity and development cycle times.

•      Experience building enterprise-grade full stack platforms with complex workflows, integrations, and distributed system architectures, ideally in domains such as enterprise SaaS, digital platforms, or financial services.

•      Exposure to AI-enabled application platforms and workflow-driven systems, including intelligent user interactions, recommendations, or data-assisted decision-making features.

•      Experience with modern frontend and backend ecosystems (React/Angular with Python/Java/.NET services) and operating in high-velocity, embedded delivery environments collaborating closely with product teams.