Note: The job is a remote job and is open to candidates in USA. Harvey Nash is seeking a Full-Stack Engineer to join their Commerce AI team as a highly autonomous individual contributor. The role involves architecting, building, and deploying AI-native applications that enhance digital commerce experiences and optimize revenue.
Responsibilities
- AI-Powered Commerce Architecture: Design, build, and scale secure, AI-native applications that enhance digital commerce experiences, optimize revenue, and personalize the customer journey
- Agentic Workflow Development: Implement advanced agentic AI workflows, integrating with leading LLMs to build autonomous systems for travel planning, dynamic merchandising, customer support, and related use cases
- Protocol Implementation: Leverage the Model Context Protocol (MCP) framework to securely connect AI models with enterprise systems, booking engines, CRM platforms, and real-time data sources
- Full-Stack Execution: Write clean, maintainable, and high-performance code across the technology stack. Utilize C# and .NET for robust, high-throughput backend microservices and SvelteKit for dynamic, responsive, and accessible user interfaces
- Cloud Infrastructure: Architect and manage cloud infrastructure across multiple cloud platforms, ensuring optimal deployment, latency reduction, scalability, and cost efficiency for AI workloads in a high-traffic e-commerce environment
- System Design & Guardrails: Drive complex system design discussions, establish technical guardrails, and ensure adherence to data privacy, AI safety, and enterprise architecture standards
Skills
- Backend: Deep expertise in C# and the .NET ecosystem for building enterprise-grade APIs and highly available microservices
- Frontend: Proven track record of building interactive, performance-optimized e-commerce or consumer-facing web applications using SvelteKit or advanced Svelte
- Cloud Architecture: Hands-on experience deploying and managing production workloads across major cloud platforms, including Microsoft Azure and Google Cloud Platform (GCP)
- Frameworks: Hands-on experience working with the Model Context Protocol (MCP) to build secure ecosystem integrations for LLMs
- Agentic AI: Demonstrated experience designing autonomous agents, multi-agent orchestration, and complex tool-use/function-calling paradigms
- Model Proficiency: Deep understanding of API integration, fine-tuning approaches, and retrieval-augmented generation (RAG) using leading LLM platforms
- Professional software engineering experience
- Dedicated experience building and scaling production-grade AI-native or LLM-powered applications
- Strong background in system design, specifically balancing trade-offs among latency, cost, and accuracy when integrating AI into revenue-generating e-commerce workflows
- Proven success as an individual contributor in fast-paced, agile environments
- Experience building complex, high-transaction e-commerce systems involving dynamic pricing, real-time inventory management, or high-scale loyalty programs
- Experience building complex reasoning pipelines, semantic routing architectures, or custom retrieval logic to provide AI agents with complex enterprise business rules
- Knowledge of LLM monitoring, evaluation, and observability tools
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