Own the end-to-end technical strategy for an agentic catalog platform, combining distributed systems, data pipelines, and AI/ML-driven automation to ingest, normalize, enrich, and validate product content at scale.
Lead, organize, and scale a multi-team engineering organization of approximately 40+ total reports (including managers and senior ICs), setting clear goals, establishing robust operating mechanisms, and developing talent.
Deliver platform reliability and quality by setting and meeting availability, latency, and accuracy SLAs; mature on-call, incident response, observability, and data-quality guardrails.
Partner cross-functionally with Product, ML, Data Science, and Operations to prioritize roadmaps, run experiments, and ship features that improve discovery, search relevance, substitution quality, pricing accuracy, and regulatory compliance.
Drive build/buy decisions, vendor selection, and budget stewardship for key capabilities (e.g., vector search, embeddings, OCR, image understanding, and content moderation) while ensuring privacy, security, and brand safety.
Champion a culture of transparency, inclusion, and continuous improvement—aligning teams to clear outcomes, sharing progress openly, and celebrating wins that grow the pie for customers, shoppers, retailers, and brands.

Requirements

15+ years of professional software engineering experience building and operating large-scale platforms or data-intensive systems.
7+ years of experience leading engineering managers and multiple teams, with direct responsibility for organizations of 30+ engineers.
Proven experience delivering large-scale data pipelines and services (batch and streaming) in cloud environments (e.g., AWS or GCP), including event-driven architectures and microservices.
Demonstrated ownership of platform reliability and data quality with defined SLAs/SLOs, on-call practices, and incident management.
Track record shipping production systems that leverage ML/AI (e.g., LLMs, information retrieval, content understanding, or automated data enrichment) and integrating them into user-facing or platform workflows.
Experience hiring, coaching, and performance-managing engineering managers and senior engineers; building diverse, high-performing teams.
Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
Strong cross-functional collaboration experience with Product, Data Science/ML, and Operations to define roadmaps and deliver measurable business outcomes.

Benefits

Annual equity grants
Highly market-competitive compensation
Flexible work arrangements

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

software engineeringdata pipelinesAI/MLcloud environmentsevent-driven architecturesmicroservicesplatform reliabilitydata qualityincident managementlarge-scale platforms

Soft Skills

leadershipcross-functional collaborationteam buildingcoachingperformance managementorganizational skillscommunicationtransparencyinclusioncontinuous improvement

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in Engineeringrelated technical field