Architect the platform to scale predictably across customers, workloads, and data volumes.
Lead capacity planning across compute, storage, databases, networking, and AI infrastructure.
Establish load, stress, endurance, and performance-testing standards.
Identify and eliminate architectural and performance bottlenecks.
Maintain performance benchmarks and ensure the platform meets enterprise-scale requirements before production.
Cost Efficiency
Define and track platform unit economics, including cost per transaction, workflow, and AI execution.
Establish cost targets and identify the primary drivers of platform economics.
Optimize model selection, routing, caching, batching, and reuse.
Move workloads from expensive LLM reasoning to code, ML, smaller models, or deterministic systems where appropriate.
Improve infrastructure utilization and eliminate unnecessary computation.
Ensure the platform remains economically viable as workload volume and complexity scale.
Qualifications
Experience: 10+ years of experience architecting and building enterprise SaaS platforms or similarly complex production systems.
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Technical Skills
Deep expertise in distributed systems, reliability, scalability, performance, and cloud architecture.
Strong experience with Azure or other hyperscale cloud platforms.
Strong understanding of databases, APIs, networking, storage, containers, and distributed compute.
Familiarity with AI/LLM infrastructure, model APIs, inference architectures, and AI economics.
Experience with observability, load testing, capacity planning, resilience engineering, and disaster recovery.
Ability to make sound architectural tradeoffs across reliability, performance, complexity, and cost.
Ability to lead architecture and drive execution across multiple engineering teams.
Benefits
Competitive Compensation: Tailored to your experience and skill set.
Flexible Work Arrangements: Hybrid working model for work-life balance.
Career Growth: Opportunities for professional development and leadership roles.
Innovative Culture: Work on transformative technologies and make an impact in the AI space.
