Commerce is seeking an AI Staff Engineer to play a pivotal role in shaping and executing our AI vision, driving strategic initiatives and delivering results through cutting-edge AI technologies.
Requirements
- Deep understanding of and experience with RAG pipelines, MCP, AI agents, multimodal LLMs, prompt orchestration, LLM telemetry and inspection, etc.
- 10+ years of coding experience in one or more server-side languages (Python, GoLang, Java, etc)
- Proven experience architecting and building AI/ML systems, especially in production environments dealing with structured and unstructured data
- Experience building product solutions with LLMs and GenAI technologies
- Familiarity with modern AI infrastructure (e.g., vector databases, model orchestration tools, inference frameworks, cloud-native ML workflows) is preferred
- Expertise in cloud platforms (AWS, GCP, or Azure), API architecture, and modern MLOps practices.
- Solid experience with SQL, in-memory storage and similar data storage solutions
Responsibilities
- Architect and build frameworks / scaffolding that provide foundational infrastructure and reusable components to power innovative AI-driven solutions.
- Collaboratively author high level designs and partner with key leaders to drive development and implementation of low level designs across teams.
- Facilitate quick-turnaround solutions to address urgent business needs, striking the right balance between delivery speed, scalability, and reliability.
- Collaborate with Product & Engineering leadership to help shape the AI strategy.
- Assess technology options to establish fit for purpose and make selections to optimize ROI for the business.
- Build scalable solutions and systems that are secure, cost-effective and performant at very large scale.
- Upskill the organization by evangelizing technologies and identifying opportunities for experimentation and education.
Other
- Highly accountable, and impact-driven
- Exceptional written and verbal communication skills
- An ability to translate vision into high level designs
- A strong bias for action
- A focus on measurable outcomes
