Jobs at Qodo

Own enterprise deployments of Qodo’s Kubernetes-based platform in customer-managed AWS, GCP, and Azure environments. Install, configure, upgrade, troubleshoot, and optimize infrastructure, writing Python or Bash diagnostics and codifying repeatable processes with Terraform and Helm. Partner directly with customer engineering teams, resolve complex networking and access issues, maintain PostgreSQL and Redis infrastructure, and improve deployment reliability through automation and documentation.

Partner with US managers on org design, hiring, performance, and employee relations. Own full-cycle US recruiting and build structured hiring processes. Design and run People programs (onboarding, manager enablement, performance, engagement). Ensure compliant US People operations and payroll coordination. Identify and implement AI and automation opportunities across HR and recruiting workflows.

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.

Lead design and implementation of MCP servers, APIs, SDKs, and cloud marketplace integrations. Translate partner asks into concrete integration plans, ship production integrations, own docs/SDKs/API DX, and create a repeatable integration playbook to scale partner integrations.

Own product lifecycle for AI developer tools, conduct customer discovery, define requirements, collaborate with engineering and design, enable sales, run experiments and metrics, drive cross-functional launches, and advocate for developer workflows.

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.

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.

Support product team with product-usage analytics, build and maintain modeled data layers and dashboards, run deep-dive analyses to inform product decisions and experiments, measure conversion/retention/churn and unit economics, and translate findings into clear recommendations for non-technical stakeholders.