Senior Fullstack Engineer

Who is Recruiting from Scratch:

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.

Senior Fullstack Engineer
Location - San Francisco, CA (Onsite - 5 Days per Week)
Compensation - $180,000 - $250,000 Base + Competitive Equity
Visa - Visa Sponsorship Available (H1B, Canadian, Australian & Singaporean Visas)
Company Stage - Series B (~$80M Raised)
Industry - AI Infrastructure, Audio AI, Machine Learning, Data Platform, Enterprise AI
About the Company

The company is building the world's first AI-native audio data research platform, enabling leading AI labs and enterprise organizations to create high-quality training datasets that power next-generation speech and audio AI systems.

Its platform combines large-scale data infrastructure, machine learning, LLMs, and advanced audio processing to help frontier AI companies build more accurate and reliable speech models. Already trusted by many of the world's leading AI labs and FAANG companies, the platform processes massive volumes of audio data while continuously improving data quality and model performance.

Backed by leading venture investors including NVIDIA and Meritech, and founded by former Scale AI leaders, the company has rapidly scaled from a small founding team to one of the fastest-growing AI infrastructure startups while maintaining an exceptionally high engineering bar.

As a Senior Fullstack Engineer, you'll build and scale customer-facing products, backend systems, and AI-powered workflows while working closely with ML researchers, customers, and engineering leadership to solve complex problems around audio data at massive scale.

This is a rare opportunity to join one of the fastest-growing AI infrastructure companies where you'll directly influence product direction, engineering culture, and the future of AI data infrastructure.
What You'll Do

• Lead end-to-end development of customer-facing product features across frontend and backend systems
• Build and scale backend services processing terabytes of production audio data
• Develop AI-powered product experiences leveraging LLMs, DSP, and modern ML technologies
• Design scalable APIs and backend architecture supporting large-scale data processing
• Build user-facing applications using modern full-stack technologies
• Collaborate closely with ML researchers to improve data collection, processing, and quality
• Deploy and evaluate AI-powered solutions for customer-facing workflows
• Build production infrastructure supporting large-scale AI data pipelines
• Partner directly with customers to understand product needs and iterate rapidly
• Mentor engineers through code reviews and engineering best practices
• Contribute across the full technology stack while maintaining high engineering quality
• Own product features from initial concept through production deployment

Ideal Candidate Background
Experience Requirements

• 4+ years of experience in backend-leaning full-stack software engineering
• Open to Staff Engineers (~6+ YOE)
• Strong sweet spot around 4-8+ years of experience
• Experience building and shipping production customer-facing software
• Experience working in high-growth VC-backed startup environments
• Experience building systems that process large-scale datasets
• Experience owning product features from concept through production deployment
• Technical leadership or engineering management experience required for Staff-level candidates
• Startup experience strongly preferred
• Demonstrated ownership of high-impact technical initiatives

Technical Requirements

• Strong TypeScript and Python engineering skills
• Experience building production full-stack applications
• Strong backend architecture and API design fundamentals
• Experience building scalable backend systems for large-scale data processing
• Familiarity with AI/ML systems, LLMs, or audio data platforms
• Comfortable working across frontend and backend technologies
• Experience building customer-facing production software
• Strong debugging, testing, and software engineering best practices
• Experience working with large datasets and distributed backend systems
• Strong product engineering mindset with backend emphasis

Education

• Bachelor's degree in Computer Science, Software Engineering, or related technical field required
• Strong academic background from a respected engineering program preferred

Soft Skills

• Strong communication skills
• High ownership mentality
• Excellent collaboration with technical and non-technical stakeholders
• Comfortable operating in ambiguity
• Self-directed and proactive
• Bias toward execution
• Startup mentality
• Strong engineering craftsmanship
• Customer-first product mindset

Preferred Backgrounds

• Scale AI
• OpenAI
• Anthropic
• ElevenLabs
• AssemblyAI
• Deepgram
• AI infrastructure startups
• Audio AI companies
• Enterprise AI startups
• Early-stage venture-backed startups
• Product engineering organizations
• Engineers building AI-powered customer products

Compensation & Benefits

• Base Salary: $180,000 - $250,000
• Competitive Equity Package
• Direct collaboration with ML researchers and engineering leadership
• Significant ownership over customer-facing product development
• Opportunity to build foundational AI infrastructure products
• High-impact engineering role
• Exposure to cutting-edge AI, LLM, and audio technologies
• Rapid career growth opportunities
• Onsite collaboration with a world-class engineering team
• Visa Sponsorship Available

Why Join

This is an opportunity to build the products and infrastructure powering one of the fastest-growing AI data platforms in the industry.

You'll develop customer-facing applications, scalable backend systems, and AI-powered workflows while collaborating closely with machine learning researchers and enterprise customers solving challenging real-world AI data problems.

As one of the early senior product engineers, you'll have outsized ownership over critical product initiatives while helping build infrastructure trusted by leading AI labs and enterprise customers.