AI Lead Software Engineer - Remote

📋 Description

• • Lead the design and implementation of multiple AI-based product solutions leveraging LLMs and GenAI technologies across the Commerce ecosystem, including BigCommerce, Feedonomics, and Makeswift.
• • Collaborate with senior Product and Engineering leaders to shape and execute the company’s AI strategy, ensuring alignment with business goals and technical feasibility.
• • Serve as the lead engineer on major AI initiatives, translating high-level architectural designs into detailed, executable low-level implementations across cross-functional teams.
• • Interface directly with stakeholders across engineering, product, design, and data science to provide technical guidance, context, and direction for AI-driven initiatives.
• • Build and optimize scalable, secure, and performant AI systems capable of operating at large scale, with a focus on cost-effectiveness and reliability.
• • Design and implement RAG pipelines, AI agents, multimodal LLM workflows, prompt orchestration systems, and LLM telemetry and inspection frameworks.
• • Leverage modern AI infrastructure including vector databases, model orchestration tools, inference frameworks, and cloud-native ML workflows on AWS, GCP, or Azure.
• • Develop and maintain data pipelines integrated with e-commerce taxonomies and schemas to enable accurate, context-aware AI outputs.
• • Evaluate and select technology options to maximize ROI, balancing speed of delivery with long-term scalability and maintainability.
• • Evangelize AI technologies across the organization through mentorship, coaching, and knowledge-sharing to upskill engineering and product teams.
• • Facilitate rapid prototyping and deployment of AI solutions to address urgent business needs while maintaining standards for quality and performance.
• • Contribute to frontend development using React, TypeScript, or JavaScript, ensuring seamless integration of AI features into consumer-facing interfaces.
• • Apply expertise in SQL and NoSQL data storage solutions to support both backend AI systems and frontend data persistence requirements.
• • Drive adoption of modern MLOps practices to streamline model deployment, monitoring, and iteration cycles.
• • Act as a technical authority on agentic commerce solutions, guiding teams in building autonomous, decision-making AI systems that enhance customer experiences.
• • Ensure all AI systems are built responsibly, with attention to ethical implications, data privacy, and transparent decision-making.
• • Partner with leadership to assess emerging AI technologies and identify opportunities for experimentation and innovation within the commerce domain.