Staff Software Engineer - Supernal

STAFF SOFTWARE ENGINEER ABOUT SUPERNAL Supernal helps small-to-medium businesses hire their first AI employee. Our AI teammates are built using intelligent, agentic workflows deployed on a proprietary platform. We deliver working, value-generating AI Employees—not tools—that handle real business processes alongside human teams. 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 commens