Staff Software Engineer

Staff Full Stack Engineer

Location: New York City or San Francisco, CA
Employment Type: Full-time
Focus: Full-Stack Engineering, Audio AI, Data Infrastructure, AI/ML Tooling
Experience: 6+ years

About Our Client

Our client is building the data infrastructure behind the next generation of audio AI.

The company is creating high-quality datasets with the same level of rigor that leading AI labs bring to model development. Their work sits at the intersection of audio, speech, data infrastructure, machine learning, generative AI, and product engineering.

Their belief is simple: audio is one of the key gateways for bringing AI into the real world. Speech is natural, accessible, and already embedded in how people communicate. As voice and audio models become more capable, high-quality training data is becoming one of the industry’s biggest bottlenecks.

Founded by former Scale AI engineers and operators, our client has already brought on leading FAANG companies and AI labs as customers and raised a $50M Series B from top-tier investors.

About the Engineering Team

The engineering team builds the systems that transform massive amounts of raw audio into high-signal training data for leading AI companies.

The work spans:

• Product engineering

• Distributed systems

• Data infrastructure

• Machine learning

• Generative AI

• Digital signal processing

Engineers operate with high ownership, move quickly, and work across the stack. The team collaborates directly with researchers and operations teams, ships production software frequently, and builds systems that process terabytes of speech data.

About the Role

Our client is hiring a Staff Full Stack Engineer to help lead the development of products and infrastructure used to understand, evaluate, and manage the audio datasets powering advanced AI models.

This is a highly hands-on role for a senior technical builder who can lead complex full-stack projects, establish engineering standards, mentor engineers, and work directly with researchers to turn ideas into production systems.

The right candidate combines strong product instincts with deep technical execution. They can move from prototype to polished product quickly without sacrificing quality.

What You’ll Do

• Lead full-stack product development across customer-facing and internal platforms

• Build scalable systems capable of processing and analyzing terabytes of audio data

• Rapidly prototype, ship, and iterate based on customer, researcher, and operations feedback

• Deploy and evaluate LLM, ML, and DSP-based systems for understanding and enriching audio datasets

• Build interfaces and tooling that help researchers and operations teams collect, evaluate, and manage data at scale

• Own technical architecture and major engineering decisions across the product

• Raise the engineering bar through architecture reviews, technical standards, and mentorship

• Identify emerging technologies across software engineering, AI, data infrastructure, and signal processing

• Help shape the engineering organization as the company continues to scale

What We’re Looking For

• 6+ years of product-focused full-stack engineering experience

• Strong fundamentals across modern frontend and backend development

• Experience building products from rapid prototypes through scalable production systems

• Track record of shipping software that creates measurable customer value

• Strong product judgment and an eye for intuitive, polished user experiences

• Experience working in fast-moving startup or high-growth engineering environments

• Ability to own ambiguous technical problems from architecture through deployment

• Experience providing technical leadership, mentorship, or engineering management

• High attention to detail without sacrificing speed

• Curiosity and ability to learn quickly in technical domains such as audio, AI, ML, and data infrastructure

Previous audio or AI/ML experience is not required. Our client cares more about technical horsepower, product judgment, curiosity, and the ability to learn quickly.

Bonus Experience

• Experience with digital signal processing, speech, or audio systems

• Experience building or deploying machine learning models in production

• Experience working with LLMs or modern generative AI systems

• Experience leading engineering teams in high-growth startup environments

• Experience building large-scale data processing systems or distributed systems

Technology

Relevant technologies include:

• Next.js

• TypeScript

• Tailwind CSS

• Node.js

• tRPC

• PostgreSQL

• AWS

• Trigger.dev

• WebRTC

• FFmpeg

Experience with every tool is not required. Strong engineering fundamentals matter more than exact stack match.

Why This Opportunity

• Join a heavily funded, fast-growing AI company while the engineering team is still small enough for individual impact

• Work on technology used by some of the most sophisticated AI labs and enterprise customers in the world

• Build at the intersection of product engineering, data infrastructure, AI, ML, and audio

• Own meaningful technical decisions across customer-facing products and internal systems

• Work directly with researchers and operators on high-impact production systems

• Help build the infrastructure and datasets that power the next generation of speech and audio intelligence

Benefits

• Unlimited PTO

• Comprehensive health, dental, and vision coverage, with 100% coverage for most plans

• FSA and HSA access

• 401(k) access

• Lunch and dinner provided, plus snacks and beverages in office

• Company-sponsored fitness benefits

Ideal Candidate Profile

The ideal candidate is a Staff-level full-stack engineer who is still deeply hands-on.

They have strong product instincts, technical range, and the ability to lead complex engineering work from ambiguity to production. They care about polished user experiences, scalable systems, and building products that create real customer value.

This person should be excited to build in a fast-moving AI environment where audio, data infrastructure, research, and product engineering all come together.