AI Platform Architect for New Product Primitives

We Love AI Jobs; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Job summary

Wispr is building the voice interface for computing. As a System Architect for new products, you will design core primitives for agentic systems—memory, context, tools, and execution—shaping a reference architecture used across product and ML teams in a fast-growing San Francisco environment.

You’ll create reusable infrastructure for prototyping, training, and evaluating models, ensure production readiness with observability, security, and cost controls, and collaborate with product, ML, client,

Qualifications

• Experience designing and shipping greenfield systems from ambiguous problems into production.
• Proven ability to design shared primitives adopted by multiple teams.
• Strong background in backend/distributed systems with scaling and reliability requirements.
• User-centered focus on latency, privacy, and trust.
• Ability to communicate architecture and tradeoffs clearly across product/ML teams.

Responsibilities

• Build shared primitives for agent development, including memory, context management, tools, and background execution.
• Create infrastructure for prototyping, training, and evaluating models.
• Develop systems for triggers and context capture across devices and modalities.
• Design harnesses for coordination and execution handoff between models.
• Make systems reliable and production-ready with observability, recovery, security, and cost controls.

Skills

Agentic systems

Memory systems

Context management

Distributed systems

Model evaluation infrastructure

Background execution

Observability

Developer tooling

Job description

Wispr is building the voice interface for computing. As a System Architect for new products, you will design core primitives for agentic systems—memory, context, tools, and execution—shaping a reference architecture used across product and ML teams in a fast-growing San Francisco environment.

You’ll create reusable infrastructure for prototyping, training, and evaluating models, ensure production readiness with observability, security, and cost controls, and collaborate with product, ML, client,