Engineering Manager, Software

📋 Description

• Lead, mentor, and develop a team of engineers responsible for creating the platform, pipelines, and interfaces that facilitate catalog enrichment and machine learning access to catalog data.

• Establish and implement the technical roadmap, balancing investments in new platform features with reliability, observability, and a positive developer experience for an expanding user base.

• Create and manage an AI-native enrichment platform that integrates large language models, traditional machine learning, rules, workflow orchestration, and human review into user-configurable pipelines.

• Propel the transition towards autonomous pipeline creation, allowing users to articulate objectives in plain language while the system constructs, assesses, and optimizes workflows.

• Oversee the machine learning-facing catalog data layer, which includes canonical product metadata and the policy controls that distinguish internal model inputs from customer-facing applications.

• Collaborate with machine learning, search, advertising, commerce, and retail teams to optimize data flows from end to end and eliminate integration barriers.

• Promote clear, human-readable controls for source prioritization, rights management, licensing, and compliance to ensure governance that is auditable.

• Enhance the productivity of developers and operators through AI-driven integration testing, investigative tools, and on-call automation; establish and achieve service level agreements on core attributes and model utilization.

• Actively participate in architectural discussions, design reviews, and code evaluations, particularly in new or exploratory domains.

⛳️ Requirements

• A minimum of 7 years of software engineering experience, including over 2 years in a managerial role leading engineers.

• Proven experience in leading teams that develop and maintain production data or machine learning platforms, encompassing both batch and streaming components.

• A solid understanding of distributed systems, data pipelines, and workflow orchestration, with demonstrated experience in build/buy/partner decision-making.

• Accountability for data quality, coverage, or compliance commitments, supported by examples of frameworks and processes utilized to fulfill these commitments.

• Exceptional written and verbal communication skills, with the ability to convey complex technical concepts to varied audiences.

• Experience with catalog, commerce, or product data platforms that operate at a significant scale.

• Practical experience with workflow orchestration systems (e.g., Temporal, Airflow, Flink) and managing them in a production environment.

• Experience in deploying applied AI/ML features in production, with an understanding of trade-offs among large language models, traditional machine learning, deterministic rules, and human review.

• Demonstrated success in collaborating across machine learning, product, and operations sectors to achieve outcomes that necessitate alignment and shared objectives.

• Knowledge of data governance, rights management, and licensing controls in environments with multiple stakeholders.

• Experience in creating pipeline builders, low-code/no-code tools, or internal platforms designed for non-engineers.

• Background in developer productivity tools, including AI-enhanced testing and investigative workflows.

• Proven ability to thrive in rapidly growing settings where both the platform and team are in a state of evolution.

🏝️ Benefits

• Highly competitive market compensation

• Equity grant for new hires

• Annual refresh grants