Qodo builds an AI-driven code review platform using LangChain, LangGraph, and multi-cloud LLM infrastructure (Vertex AI, SageMaker, Bedrock). The tech stack signals a mature ML ops posture: Prometheus, Grafana, Datadog, and container orchestration (Kubernetes, ArgoCD) across GCP, AWS, and Azure. Active hiring skews heavily toward senior engineering (13 of 21 roles), paired with pain points around production ML infrastructure and LLM system security—suggesting they're scaling beyond prototype toward hardened, multi-tenant deployments.
Tech Stack 57 technologies
Core StackPython FastAPI PostgreSQL Redis Kubernetes Docker AWS Helm ArgoCD Terraform Prometheus Grafana Elasticsearch Datadog LangChain Vertex AI SageMaker GCP AWS EKS Azure Kubernetes Service Terragrunt Azure SAST DAST Bash IAM LiteLLM LangGraph LangSmith Bedrock+24 more
What Qodo Is Building
◆Challenges
- Go-to-market engine scaling
- Mql-to-deal conversion improvement
- Acquiring new commercial customers
- Hardening cloud configurations
- Technical concerns and objections
- Securing llm systems
- Cloud posture management
- Reducing operational costs
- Scalable ml infrastructure
- Transform experimental concepts into production-ready systems
▲Active Projects
- Clay enrichment framework
- Ai-driven enrichment initiatives
- Hubspot lifecycle strategy
- Ai code review platform
- Llm prompt pipeline backend
- Threat modeling
- Security program scaling
- Llm system security
- Cloud posture management
- Design and build comprehensive ml pipelines
Hiring Activity
20 roles · 10 in 30d
Department
Seniority
Notable leadership hires: Tech Lead
Company intelligence
