Full Stack Engineer, Commerce AI

Spectraforce
Seattle, WA, United States
5 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

.NET Framework Application Programming Interfaces (APIs) Artificial Intelligence Microsoft Azure C Sharp (Programming Language) Cloud Computing Cloud Engineering Design of User Interfaces Performance Tuning Svelte Software Safety Software Engineering
+12 more
Systems Integration Web Applications Google Cloud Large Language Models Grafana Multi-Agent Systems Generative AI Backend Integration Frameworks Front End Software Development Virtual Agents Microservices

Job description

We are seeking a Senior Full Stack Engineer to join our Commerce AI team as highly autonomous individual contributors. In this role, you will architect, build, and deploy AI-native applications that directly impact the booking flow, dynamic pricing models, and personalized guest experiences. You will combine deep, traditional full-stack engineering with hands-on orchestration of Agentic AI systems using modern LLMs and integration frameworks., * AI-Powered Commerce Architecture: Design, build, and scale secure, AI-native applications that enhance the digital storefront, optimize revenue, and personalize the guest journey.

  • Agentic Workflow Development: Implement advanced Agentic AI workflows, integrating with leading LLMs (Gemini, OpenAI, Anthropic) to build autonomous systems for travel planning, dynamic merchandising, and guest support.
  • Protocol Implementation: Leverage the Model Context Protocol (MCP) framework to seamlessly and securely connect AI models with our enterprise flight and booking engines, CRM systems, and real-time flight data.
  • Full-Stack Execution: Write clean, maintainable, and high-performance code across the stack. You will utilize C# (.NET) for robust, high-throughput backend microservices and SvelteKit for dynamic, responsive, and accessible user interfaces.
  • Dual-Cloud Infrastructure: Architect and manage cloud infrastructure across Azure and GCP, ensuring optimal deployment, latency reduction, scaling, and cost-efficiency of AI workloads in a high-traffic e-commerce environment.
  • System Design & Guardrails: Drive complex system design discussions, establish technical guardrails, and ensure strict adherence to data privacy, AI safety, and enterprise architecture standards.

Requirements

  • Backend: Deep expertise in C# and the .NET ecosystem for building enterprise-grade APIs and highly available microservices.
  • Frontend: Proven track record 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 in both Microsoft Azure and Google Cloud Platform (GCP).

AI & Emerging Tech

  • 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 orchestrations, and complex tool-use (function calling) paradigms.
  • Model Proficiency: Deep understanding of API integration, fine-tuning patterns, and retrieval-augmented generation (RAG) using Gemini, OpenAI, and Anthropic models.

Professional Experience

  • 8+ years of professional software engineering experience.
  • 3+ years of dedicated experience building and scaling production-grade AI-native or LLM-powered applications.
  • Strong background in System Design, specifically balancing the trade-offs of latency, cost, and accuracy when integrating AI into revenue-generating e-commerce flows.
  • 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 (airline/travel industry experience is a bonus, but not required).
  • Experience building complex reasoning pipelines, semantic routing architectures, or custom retrieval logic to supply AI agents with complex enterprise business rules.
  • Knowledge of LLM monitoring, evaluation, and observability tools

Apply for this position

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