Staff Platform Systems Engineer

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