Senior Backend Engineer - Workforce AI Security

Why Join Us?

We are building a next-generation Workforce AI Security platform that helps enterprises manage, secure, and govern

AI-powered products at scale.

We are looking for a Senior Backend Engineer to join the core backend team and own foundational services used across the

platform. The role is focused on production-grade backend engineering, distributed systems, APIs, reliability, and clean,

maintainable design

Key Responsibilities

• Design, build, and own backend services from design to production.
• Build secure, scalable APIs and microservices for core platform capabilities.
• Work on domains such as policy flows, identity/authentication, tenant and license management, client/agent services, MCP protection, analyzers, and business-logic services.
• Design reliable flows for service-to-service communication, caching, background processing, data persistence, and multi-region production environments.
• Participate in architecture discussions and improve system design, performance, security, reliability, and observability.
• Write clean, maintainable, well-tested code and take ownership of delivery quality.
• Collaborate closely with product, architects, frontend, DevOps, security researchers, and other engineering teams.
• Troubleshoot production issues and contribute to strong engineering standards and best practices.
  
  

• 4+ years of hands-on software development experience, with strong backend ownership.
• Strong proficiency in Python and backend frameworks such as FastAPI or similar.
• Solid experience designing REST APIs, backend services, and production SaaS/cloud-native systems.
• Good understanding of distributed systems, asynchronous processing, caching, data modeling, and service-to-service communication.
• Experience with relational databases, preferably PostgreSQL, including schemas, migrations, ORMs, and performance considerations.
• Experience with Redis or similar caching/message-oriented infrastructure.
• Knowledge of Git, CI/CD, Docker, Kubernetes-based deployment, and cloud platforms such as AWS.
• Strong debugging skills, practical production mindset, independent ownership, and effective collaboration.