Senior/Staff Software Engineer, AI/ML

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/Staff Software Engineer, AI/ML

Location

New York, NY / San Francisco, CA / Seattle, WA (Hybrid or Remote Eligible)

Company Stage of Funding

Late-Stage Growth / Series F+

Office Type

Hybrid (NYC 3x/week) or Remote in approved hub cities

Salary

$220,000 – $300,000 + Competitive Equity

Visa

No sponsorship available

Company Description

Our client is building the world’s largest virtual clinic for women and families, serving over 2,000 employers and health plans globally.

They are becoming an AI-native healthcare organization and are building foundational AI infrastructure that powers critical experiences across their platform — including chatbots, recommendation engines, search, intelligent workflows, and GenAI-powered healthcare experiences.

Backed by top-tier investors including Sequoia, General Catalyst, Dragoneer, and Lux Capital, the company has raised over $425M and is operating at massive scale across fertility, maternity, pediatrics, menopause, and family healthcare.

This is an opportunity to join a foundational AI engineering team where you will directly shape the future of AI-powered healthcare products used by millions of users.

What You Will Do

Design, build, and deploy end-to-end AI-powered applications and infrastructure

Build production-grade LLM systems using RAG, agent frameworks, orchestration layers, and modern AI tooling

Develop AI-powered chatbots, recommendation engines, search systems, and intelligent workflows

Own AI/ML product development from 0-to-1, from architecture through production deployment

Design scalable ML pipelines for experimentation, fine-tuning, evaluation, and deployment

Work closely with product, data, analytics, and engineering teams to deliver AI-native product experiences

Build backend systems and APIs supporting AI workloads and inference pipelines

Drive technical architecture and engineering best practices across AI systems

Work with modern AI platforms including OpenAI APIs, Vertex AI, PyTorch, TensorFlow, and agent frameworks

Translate healthcare and user data into intelligent, production-ready AI systems

Contribute to AI platform strategy and help shape the company’s long-term AI roadmap

Operate autonomously in a fast-moving, highly ambiguous AI product environment

Balance rapid iteration with scalability, safety, reliability, and performance

Collaborate cross-functionally with product and business stakeholders to identify impactful AI opportunities

Stay current with emerging LLM, RAG, and agentic AI technologies and integrate them into production systems

Ideal Candidate Background

6–15 years of experience in software engineering or AI/ML engineering roles

Strong software engineering foundation with backend-heavy product engineering experience

Experience building AI/ML products end-to-end in production environments

Hands-on experience with LLMs, RAG systems, and agent frameworks

Experience shipping production AI products from 0-to-1

Strong Python engineering experience

Experience with chatbot systems, recommendation engines, search, or GenAI applications

Experience working across the full ML lifecycle including ingestion, preprocessing, training, deployment, and monitoring

Strong distributed systems and backend architecture skills

Experience collaborating closely with product and cross-functional teams

Comfortable operating autonomously in fast-moving startup or high-growth environments

Strong builder mentality with high ownership and execution ability

Comfortable writing production-grade code without heavy AI tooling dependence

Ability to explain AI systems and technical tradeoffs clearly to non-technical stakeholders

Strong Signals

Experience building production LLM applications at scale

Experience with RAG architectures and retrieval pipelines in production

Experience with AI agent frameworks and orchestration systems

Experience building chatbot, recommendation, or intelligent search systems

Strong backend engineering foundation transitioning into AI/ML

Experience with OpenAI APIs, Vertex AI, LangChain, LlamaIndex, or similar tooling

Healthcare or digital health AI experience

Experience handling high-volume production AI workloads

Experience measuring production AI system performance and reliability

Strong product-minded engineering instincts

Experience working at high-growth product companies

Experience owning projects from architecture through deployment

Experience balancing ML experimentation with production engineering rigor

Strong understanding of distributed systems and scalable infrastructure

Experience working with PyTorch or TensorFlow

Strong coding interview and system design capability

Ability to discuss production metrics, scale, and operational performance of AI systems

Experience building AI features with meaningful user or business impact

Experience working on AI-powered user-facing products instead of purely internal ML infrastructure

Compensation and Benefits

Base salary

$220,000 – $300,000

Competitive equity package

Opportunity to help build foundational AI infrastructure at massive scale

Work directly on cutting-edge AI systems impacting millions of healthcare users

Exposure to advanced LLM, RAG, and agentic AI deployment challenges

Strong technical ownership and autonomy

High-growth healthcare AI company trajectory

Backed by Sequoia, General Catalyst, and other top-tier investors

Collaborative, product-focused AI engineering culture

Why Join

This is an opportunity to join one of the most ambitious AI transformations happening in healthcare today.

You’ll work on foundational AI systems powering healthcare experiences at massive scale while helping define how AI-native healthcare products get built responsibly and effectively.

If you enjoy building production AI systems, shipping 0-to-1 AI products, solving hard engineering problems, and operating at the intersection of backend engineering and modern AI infrastructure, this role offers exceptional scope and impact.