Jobs at Qodo

Build developer-first integrations and backend systems, own projects end-to-end, drive architecture and engineering practices, mentor teammates, and collaborate globally to integrate AI coding assistants into developer workflows.

Lead end-to-end U.S. recruiting for GTM and Engineering roles, build sourcing pipelines, partner with hiring managers, improve candidate experience and onboarding, manage U.S. benefits administration, and use analytics and AI tools to optimize hiring.

Design, implement, and maintain backend features end-to-end for a scalable AI-driven SaaS platform. Debug complex production systems, collaborate with product and engineering, ensure performance, reliability, and code quality, and leverage modern AI tools to improve development and review workflows.

Design and implement MCP servers, public APIs, SDKs, and cloud/marketplace integrations for strategic partners. Own partner-facing technical scoping, ship production integrations, document and version developer-facing surfaces, and build a repeatable integration playbook to scale partnerships while maintaining excellent developer experience.

Lead full-cycle technical recruiting for Engineering, Product, and GTM roles; partner with hiring managers; build pipelines; manage interviews and offers; improve processes using data and AI; contribute to employer branding and People initiatives.

Run day-to-day operations for Qodo's Tel Aviv office and support global hubs (Boston, NYC). Manage facilities, vendors, supplies, onboarding/offboarding logistics, travel coordination, IT equipment and first-line IT support. Partner with HR on events and team operations, maintain vendor relationships, and ensure a welcoming, functional workplace for a fast-growing AI startup.

Embed with enterprise customers to deliver on-prem and air-gapped deployments, diagnose and remediate production issues, build customer-specific extensions, upstream solutions into product, and codify playbooks to scale field engineering.

Design, develop, implement, and test algorithms and LLM-enabled solutions; collaborate with product and engineering teams; research new techniques; build benchmarks and lead algorithm development to improve product performance and scalability.

Embed with enterprise customers to design, deploy, and stabilize on‑prem AI code-review systems. Diagnose production distributed‑system issues, build customer extensions, upstream product improvements, and create playbooks, runbooks, and benchmarks to scale field engineering.