Job Description

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 commensurate with experience (Staff/Principal level)
• Location: Remote
• Type: Full-time
• Requirements: Overlap with Americas timezones for collaboration; reliable high-speed internet