• Lead and scale a distributed engineering organization across core database infrastructure, cloud platform, and developer experience — owning hiring, culture, and team design • Partner with the leadership team on product roadmap and architectural decisions, translating company strategy into executable engineering plans • Drive reliability, performance, and velocity across Qdrant's core engine, Qdrant Cloud, Hybrid Cloud, and emerging products like Cloud Inference and Qdrant Edge • Establish engineering excellence: code quality standards, incident response, observability, and the operational rhythm needed to run a production database at scale • Work closely with Product, Developer Relations, and Customer Success to ensure engineering efforts are tightly aligned with the needs of Qdrant's developer community and enterprise customers • Define and own the engineering hiring plan to meet aggressive growth targets, with a focus on Rust, distributed systems, and ML infrastructure talent • Champion a culture of rigor, ownership, and craft — the kind of culture that builds a custom storage engine from scratch because the off-the-shelf solution isn't fast enough

• Lead and develop a multidisciplinary engineering team, fostering a culture of technical excellence, ownership, and continuous improvement. • Mentor engineers at all levels, supporting their growth through coaching, feedback, and clear expectations. • Own the full lifecycle of integrations with PSPs, acquirers, and gateways, from technical design to deployment and production monitoring. • Drive hands-on technical contribution through architecture design, code reviews, and complex troubleshooting, setting the technical bar for your team. • Set and enforce best practices across coding standards, testing, observability, and documentation. • Ensure the team follows secure software development practices, including OWASP standards, data privacy, and compliance requirements. • Guide architectural decisions for low-latency, high-availability backend systems and microservices. • Champion an AI-first engineering culture, setting standards for AI-assisted development, code generation, and automated testing, ensuring your team leverages these tools as a default, not an afterthought. • Collaborate closely with Product, Compliance, and Business teams in an agile environment to deliver against a fast-moving roadmap. • Drive the evolution of APIs and integration frameworks that scale across countries and providers.

• Lead and manage the development team setting development standards while remaining deeply hands-on in coding and architecture • Own the end-to-end development lifecycle, from design through delivery and iteration • Drive execution of product roadmap items, ensuring timely and high-quality releases • Oversee ongoing system maintenance, stability, and performance, including: Bug fixes and issue resolution, Continuous improvements and enhancements, Proactive monitoring and technical debt management • Define and enforce engineering best practices, coding standards, and development processes • Architect scalable, reliable, and secure systems • Collaborate cross-functionally with product, leadership, and stakeholders • Mentor and grow engineers, fostering a culture of ownership and technical excellence • Partner with customers and internal stakeholders to support: Proof of Concepts (POCs), Proofs of Technology (POTs), Technical validation and solution design efforts • Identify and implement opportunities to leverage AI in: Development productivity (e.g., tooling, automation), Product capabilities and innovation

• Lead, coach, and develop a team of 6 engineers spanning streaming, data lakehouse, serving layer, and platform infrastructure — with genuine curiosity about each domain • Serve the team by removing obstacles, shielding them from organizational noise, and ensuring they have what they need to ship • Own the quarterly plan and sprint-level execution: translate OKRs into milestones with clear owners, timelines, and success criteria — and keep them updated without being asked • Coach each engineer toward their next level, with specific plans, timely feedback, and active promotion sponsorship when the work is done • Champion engineering best practices: design reviews before major changes, ADRs for architectural decisions, blameless post-mortems, automated testing, and data quality as a first-class citizen in every pipeline • Manage the on-call rotation and incident response process so that reactive work doesn't consume the team's capacity to build • Build an understanding of the data cloud architecture — not to design it, but to ask better questions, anticipate risks, and have credible conversations with stakeholders • Foster a culture of curiosity and continuous learning, where engineers explore new technologies, share knowledge, and question assumptions • Hire exceptional talent to grow the team with a focus on diversity, raising the bar, and complementing existing strengths • Drive AI adoption across the team's engineering workflows — the team has a mandate for AI adoption, and you'll be expected to be a role model, to champion this, remove friction, and help engineers integrate AI tools into their daily development, code review, documentation, and debugging practices •