Engineering Manager | Senior | Knowledge

Job description

Join the AI revolution. We’re building an all-in-one AI platform to help teams do their best work and automate every routine task you can think of. We’re looking for problem-solvers to turn powerful AI into an easy, no-code tool for teams everywhere. ### Main Responsibilities - Lead and grow the product engineering team responsible for developing cutting-edge intelligent systems. - Enable the team to deliver high-impact, critical services across storage architecture, real-time observability, and scalable, resilient infrastructure. - Collaborate with Product Owners to prioritize and deliver robust, intuitive systems that handle complex data pipelines and advanced engineering workflows. - Align with other engineering teams to ensure synchronization and seamless development across the organization, driving innovation at scale. - Foster an excellent engineering culture guided by our company values and engineering principles, promoting continuous learning and technical excellence. - Hire, mentor, and develop team leads as the organization grows, cultivating strong technical leadership. ### Core Requirements - Senior developer background with exceptional technical skills in designing, building, and optimizing distributed systems. - Strong technical leadership experience in a fast-paced, high-growth environment, guiding teams through complex technical challenges. - Ability to collaborate effectively with product teams and other stakeholders, translating strategic goals into technical execution. - Proven track record of delivering sophisticated technical solutions, particularly those involving large-scale data processing or intelligent applications. - Deep interest in continually learning about AI technologies, machine learning infrastructure, and their practical applications. - A passion for building impactful products that leverage advanced technology to solve complex user problems. - Strong delivery focus, emphasizing technical excellence, reliability, and measurable impact. - Experience with machine learning operations (MLOps) or deploying AI/ML models in production environments is a bonus. ### Tools You'll Use - React, Go, Large Language Models (LLMs) - Distributed database technologies and advanced data stores - Cloud-native storage solutions and data lakes - Real-time observability, monitoring, and alerting platforms - Robust security frameworks and compliance practices