Engineering Lead

We are the backend engineering team for a data annotation platform that powers AI/ML workflows, including data preparation, quality control, and integration with model training pipelines. Our focus is on backend services, data workflows, platform reliability, and scalability. We collaborate closely with Applied Science, Data, Product, and other engineering teams.

We are seeking an experienced Engineering Lead to guide and manage our backend team. This role combines backend engineering leadership, stakeholder collaboration, ownership of team delivery, and people management. You will be responsible for setting technical direction, driving execution quality, developing engineers, and ensuring the reliability and scalability of engineering systems that directly support AI/ML development.

• →Lead and manage the backend team and own all aspects of delivery, including planning, execution, technical risk management, and engineering quality
• →Drive technical excellence by guiding key design decisions, resolving architectural trade-offs, and supporting the team on complex production, reliability, and scalability issues for backend services, APIs, and data workflows
• →Manage and develop engineers through regular 1:1s, performance support, coaching, and career development
• →Improve team execution by addressing technical debt, process gaps, and knowledge-sharing needs in partnership with cross-functional stakeholders (Applied Science, Data, Product, etc.)

• Proven experience leading and managing backend engineering teams
• Strong practical experience with Python backend development
• Experience designing, building, and operating production backend services, APIs, and data-processing workflows
• Practical AWS experience for building, operating, and troubleshooting production backend systems
• Experience with containerized backend systems, queues, background jobs, and/or workflow orchestration (Kubernetes experience is preferred)
• Strong system design skills focused on scalability, reliability, and maintainability
• Proven people management skills: coaching, feedback, and engineer development
• Experience with delivery planning, technical risk management, production support, debugging, monitoring, and incident resolution
• Clear and direct communication style with engineers, managers, and stakeholders
• Ability to create clarity in ambiguous situations and make pragmatic decisions that balance speed, quality, and maintainability

• Experience with data-heavy backend systems, data pipelines, or workflow-heavy platforms
• Experience in AI/ML, computer vision, MLOps, or ML-adjacent engineering
• Familiarity with security-sensitive systems, such as access control or auditability
• A product mindset, interest in user workflows, and ability to communicate technical direction to senior stakeholders