Original listing text, shown exactly as published by the company.
The Role
We're looking for a Staff/Principal Software Engineer to own and evolve the core platform that powers our AI employees. This is a technical leadership position responsible for the systems that enable our agents to scale reliably: the Django backend, distributed task infrastructure, event-driven architecture, Kubernetes deployments, and observability stack.
You'll work across the full system—from database query optimization to Helm chart tuning to designing new platform abstractions. You'll be a force multiplier for the engineering team, driving architectural decisions, eliminating scaling bottlenecks, and establishing patterns that make the platform more robust and developer-friendly.
This role reports to the Director of Engineering and involves significant autonomy in shaping technical direction.
What You'll Own
- Drive platform architecture decisions and align the team on scalable patterns and long-term maintainability
- Review a high volume of code, design docs, and architectural proposals for scalability, reliability, security, and operability
- Be a technical mentor and force multiplier: unblock engineers, raise the bar on production readiness, and establish platform best practices
- Own and evolve the core backend platform (Django/DRF/ASGI) performance and correctness
- Scale async execution across Celery + Dramatiq + Temporal/Cortex; implement resilient workflow patterns (retries, circuit breakers, graceful degradation)
- Optimize PostgreSQL/pgvector (query tuning, connection pooling) and caching strategies
- Maintain and improve Kubernetes deployment infrastructure (GKE, Helm, Terraform/OpenTofu) and CI/CD + rollout strategies. Own KEDA autoscaling policies and resource allocation across worker pools.
- Own reliability of RabbitMQ, Redis, and PostgreSQL infrastructure; lead incident response and post-mortems
- Extend OpenTelemetry + Datadog instrumentation, dashboards, alerts, and SLOs; profile and reduce latency/memory bottlenecks
What We're Looking For
Required
- 10+ years building and operating production backend systems at scale
- Deep expertise in Python (Django preferred) and relational databases (PostgreSQL)
- Hands-on experience with Kubernetes, Helm, and cloud infrastructure (GCP preferred)
- Strong background in distributed systems: message queues, event sourcing, workflow orchestration
- Production experience with async task systems (Celery, Dramatiq, or similar)
- Track record of debugging complex production issues across multiple services
- Ability to work autonomously and drive technical initiatives without close supervision
- Clear technical communication—able to explain tradeoffs and build consensus
Preferred
- Experience with Temporal or similar workflow engines
- Background in LLM infrastructure, RAG systems, or AI/ML platforms
- Familiarity with OpenTelemetry, Datadog, or similar observability stacks
- Experience with KEDA or other Kubernetes autoscaling solutions
- Contributions to multi-tenant SaaS platform architecture
- History of improving developer experience and platform abstractions
What Success Looks Like
- Platform services maintain high availability with predictable performance under load
- Scaling bottlenecks are identified and resolved proactively
- New features ship faster because platform primitives are well-designed and documented
- Incidents are rare, quickly detected, and thoroughly addressed
- Engineers across the team adopt platform patterns and best practices
- Technical debt is systematically identified and paid down
- You're a trusted technical voice in architectural discussions
Compensation & Logistics
- Compensation: Competitive salary commensurate with experience (Staff/Principal level)
- Location: Remote…
