WISEcode is a well-funded, dynamic startup focused on personalized nutrition powered by AI. They are seeking a Staff Platform Systems Engineer to lead architectural ownership and accountability across major parts of their platform, designing scalable data systems and mentoring senior engineers.
Responsibilities:
- Own architecture for core data systems, including Postgres, lakehouse layers, computation pipelines, and semantic models
- Lead solution design for high-complexity, data-intensive initiatives and deliver production-ready implementations when needed
- Define data contracts, abstractions, and platform standards that enable multiple teams to build safely and independently
- Diagnose and resolve issues across data ingestion, storage, computation, and consumption layers
- Guide schema evolution, performance optimization, data correctness, reliability, and security considerations
- Mentor senior engineers and elevate engineering culture through clarity, documentation, and principled design
- Partner closely with product, CTO, AI/ML, and engineering teams to shape roadmap feasibility and long-term platform direction
- Apply AI and analytics concepts in ways that are explainable, auditable, and grounded in well-defined data semantics
Requirements:
- BSCS or equivalent engineering degree
- 12+ years of strong professional development experience
- Demonstrated ownership of large-scale data platforms or systems whose architecture, performance, and evolution you were personally responsible for over time
- Deep expertise with Postgres, data modeling, schema design, query optimization, and data-intensive systems
- Experience designing and evolving distributed systems and computation pipelines beyond their original requirements
- Track record of technical leadership, mentoring, and cross-team influence as an individual contributor
- Ability to operate independently, set direction, and drive execution in ambiguous or under-specified contexts
- Broad systems thinking with depth in data, computation, and platform architecture
- Experience supporting AI or ML systems through data design, quality, and infrastructure (direct model training experience not required)
- Startup mind - adaptability, urgency, pragmatism, and comfort shifting between experimentation and production delivery