Hiring for a startup that turnstacit work knowledge into governed AI agents, allowing enterprises to scale their internal expertise.
You'll be a good fit if you have
- Mastery of AI-native development and automaoptimizationfault working mode.
- Expert-level proficiency in Python and Go.
- Deep technical expertise in at least four of the following domains:
- Cloud Architecture: Multi-region, compliance-heavy enterprise setups.
- Kubernetes: Platform engineering at massive scale.
- Observability: Unified metrics, agentic workflow tracing, and LLM monitoring.
- LLM Ops: Model serving, routing, and cost optimization for AI workloads.
Key Responsibilities
- Define the long-term global roadmap for multi-region, multi-tenant cloud infrastructure that meets Fortress level standards for reliability, compliance, and enterprise isolation.
- Architect and own a unified CI/CD optimizationtrategy across application code, infrastructure-as-code, ML models, and RAG pipelines, with a strong focus on Kubernetes architecture including GPU federation and cost optimization.
