Product Systems Engineer, AI Voice Interfaces

Menlo Ventures; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Wispr is seeking a senior engineer to own the hard systems at the center of our product surface, across existing products, new launches, or feature-specific initiatives. You’ll make ambiguous quality problems measurable, solve them at their root, and build approaches the team can reuse.

You’ll work on detecting, inferring, and delivering critical experiences, instrumenting difficult problems and establishing evidence of correctness when ground truth is unavailable.

Qualifications

• Shipped a complex system with interacting failure modes.
• Owned a system whose correctness was difficult to observe.
• Defined a quality metric whose meaning was contested.
• Combine systems thinking with product intuition and user empathy.
• Hands-on implementer who follows problems across boundaries.
• Detail-oriented and able to own ambiguous outcomes.

Responsibilities

• Build the detection, inference, state, and delivery systems behind critical experiences.
• Instrument difficult problems before choosing a solution.
• Establish evidence of correctness when ground truth is unavailable.
• Make principled tradeoffs across imperfect signals, edge cases, and user impact.
• Turn persistent quality problems into comprehensible, repeatable systems.
• Partner with product and platform teams to determine where systems should live.

Skills

Complex system design

Systems thinking

Quality metrics

First principles

Ambiguity handling

Cross-boundary collaboration

Job description

Wispr is seeking a senior engineer to own the hard systems at the center of our product surface, across existing products, new launches, or feature-specific initiatives. You’ll make ambiguous quality problems measurable, solve them at their root, and build approaches the team can reuse.

You’ll work on detecting, inferring, and delivering critical experiences, instrumenting difficult problems and establishing evidence of correctness when ground truth is unavailable.