Staff Software Engineer - 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.

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.

• 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

• 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

• 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

• 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