---
title: 'Solutions Engineering Lead, Healthcare & Life Sciences at Scale AI'
canonical: 'https://feeny.ai/job/solutions-engineering-lead-healthcare-life-sciences-scale-ai-new-york-phez1j5grdvm'
type: 'job'
last_seen: '2026-09-23'
---

# Solutions Engineering Lead, Healthcare & Life Sciences at Scale AI

- **Company:** Scale AI
- **Location:** New York, NY / San Francisco, CA
- **Compensation:** $212k–$265k
- **Posted:** 2026-09-17
- **Last confirmed live:** 2026-09-23
- **Apply:** https://job-boards.greenhouse.io/scaleai/jobs/4735192005

## Job description

Scale plays a vital role in the development of AI applications, and healthcare and life sciences is one of the highest stakes places that work lands. Providers, payers, pharma, biotech, and medical device companies are moving AI from pilot to production against real regulatory and patient safety constraints. They need a partner who understands both the technology and the environment it has to survive in.

As Solutions Engineering Lead for Healthcare & Life Sciences, you'll be a player-coach: managing and growing a team of 3 to 5 Solutions Engineers while personally owning our most strategic accounts in the vertical. You'll set the technical bar for how Scale sells and deploys into regulated healthcare environments, build the reusable assets and playbooks your team runs on, and be the person Sales, Product, and Engineering turn to when a deal hinges on a hard clinical or compliance question.

You will:

- Manage, coach, and grow a team of 3 to 5 Solutions Engineers, setting expectations, running deal reviews, developing careers, and hiring as the vertical scales.
- Personally own the technical win on our most strategic healthcare and life sciences accounts, staying hands-on in demos, prototypes, and architecture conversations rather than managing from a distance.
- Build the vertical's technical playbook: reference architectures, demo environments, evaluation frameworks, and SOW patterns your team and the broader GTM org can reuse.
- Serve as the domain authority on deploying GenAI under healthcare constraints, including PHI handling and de-identification, HIPAA and HITRUST, validation and audit expectations, and the realities of clinical workflow adoption.
- Partner with AEs and GTM leadership on account strategy, technical qualification, and pilot scoping that converts into production deployments.
- Work with forward-deployed Software and Machine Learning Engineers to carry solutions from initial design through early implementation.
- Translate patterns across your accounts into structured, prioritized input for Product and Engineering, and influence the roadmap on behalf of the vertical.

Ideally you'd have:

- A strong engineering background with significant experience in a customer-facing technical role (solutions engineering, solutions architecture, forward-deployed engineering, or technical consulting), including hands-on development in Python or similar.
- Experience leading or mentoring technical individual contributors. Formal people management is welcome, but a credible track record as a tech lead or team lead matters more than title.
- Direct experience selling, building, or deploying software in healthcare or life sciences, with working fluency in the regulatory and data privacy environment (PHI, HIPAA, and validation requirements).
- Presentation skills with high technical credibility in front of both clinical or executive stakeholders and front-line engineers, plus the intellectual curiosity, empathy, and velocity to operate in a fast-moving vertical.

Nice to haves:

- Hands-on GenAI, LLM, or applied machine learning experience, especially evaluation and model validation in a regulated setting.
- Clinical, biomedical, or pharma domain background (clinical informatics, EHR integration, pharmacovigilance, regulatory affairs, or R&D).
- Experience standing up a new vertical, practice, or team from an early stage.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $212,000—$265,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's [Know Your Rights poster](https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our [privacy policy](https://scale.com/legal/privacy) for additional information.

## About Scale AI

## Company Overview
- **One-liner**: Scale AI provides high-quality data, RLHF, model evaluations, and full-stack AI infrastructure to help enterprises and governments build, deploy, and oversee reliable AI systems.
- **Entity Type**: Private (49% non‑voting stake owned by Meta Platforms as of June 2025; total funding $1.6B across eight rounds)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2016
- **Founders**: Alexandr Wang, Lucy Guo (Wang left in June 2025; current CEO is Jason Droege)

## Core Business
- **Primary industry**: AI infrastructure, data annotation, large language model (LLM) evaluation, enterprise AI deployment
- **Target customers**: B2B – Enterprise and government organizations; also serves leading AI labs (e.g., OpenAI, Google DeepMind, Meta, Microsoft, General Motors)
- **Mission**: “Develop reliable AI systems for the world's most important decisions.”

## Products & Services
- **Data at Scale**: High-quality training data, annotations, and RLHF for advanced AI models (SaaS + human-in-the-loop service)
- **Evaluations**: Rigorous model evaluations, benchmarking, and red‑teaming to measure and improve AI performance (service)
- **Applied AI**: Full‑stack AI systems that help enterprises and governments build, deploy, and oversee reliable AI (SaaS + consulting)
- **Safety, Evaluation and Alignment Lab**: Research arm focused on LLM alignment and safety (internal R&D; also co‑created the “Humanity's Last Exam” benchmark)
- **Subsidiaries**: Remotasks (computer vision and autonomous vehicle data labeling), Outlier (LLM data annotation)

## Market Standing
- **Valuation**: $29B (as of 2025 – cited on scale.com)
- **Key Metric**: Total Funding – $1.6B (including the $14B Meta investment that acquired a 49% non‑voting stake in June 2025)
- **Notable Investors/Partners**: Meta Platforms (49% owner), with commercial customers including Google, Microsoft, Meta, General Motors, OpenAI, and Time. Also works with U.S. and Qatari governments.
- **Growth Signals**:
  - Headcount: Scale.com cites “1,000+” employees; LinkedIn reports 3,751 employees (+32.1% YoY).
  - 90% of the world’s leading generative AI model builders are powered by Scale.
  - 15 billion human decisions used to train AI models; $1 billion paid to contributors globally.
  - Active job postings: 284+ (as of July 2025), with strong hiring in enterprise engineering, AI agents, and solutions roles.

## Competitive Advantages
- **Data moat**: Scale’s proprietary Data Engine and access to millions of human‑annotated decisions create high‑quality training data that competitors cannot easily replicate.
- **Trust & adoption**: Used by 90% of leading GenAI builders; runs private benchmarks for the most ambitious AI companies.
- **Government credibility**: Direct contracts with the U.S. Department of Defense and international governments (e.g., Qatar) – a high‑barrier entry point.
- **Full‑stack offering**: From raw data annotation to LLM evaluation and end‑to‑end applied AI deployment, Scale covers the entire AI lifecycle.
- **Research leadership**: In‑house Safety, Evaluation and Alignment Lab; co‑creator of the “Humanity's Last Exam” benchmark.

## Strategic Focus
- **Enterprise GenAI agents**: Ramping up “AgentOps” and “Frontier Agents” engineering teams (many open roles in SF, NY, London, Budapest).
- **Healthcare & life sciences**: Hiring dedicated GTM leaders and AI strategists for healthcare vertical.
- **International expansion**: Growing offices in London, Budapest, Mexico City, and Washington DC.
- **Safety and alignment**: Continued investment in red‑teaming, model evaluations, and government‑focused AI safety contracts.

## Why Work Here
- **Mission‑driven**: “Develop reliable AI systems for the world’s most important decisions” – directly shaping frontier AI capabilities.
- **Compensation & benefits**: Comprehensive health, dental, vision, mental health services; generous PTO; annual learning & development stipend; parental leave; ERGs; guest‑friendly offices with happy hours, game nights, book clubs.
- **Engineering culture**: Credos such as “Write the Market,” “Find the 20%,” “Earn Customer Love,” and “Quality is Our Cheat Code” emphasize impact over effort, customer obsession, and structured thinking.
- **Growth trajectory**: Rapid headcount growth (+32%), major Meta investment, and expansion into new verticals signal a company in high‑growth mode.
- **Flexible work**: Offices in SF, NY, London, Budapest, Mexico City, DC; the careers page highlights “flexible environment,” though specific remote/hybrid policy is not explicitly stated.

## Sources
1. [scale.com](https://scale.com/about)
2. [scale.com](https://scale.com/)
3. [scale.com/careers](https://scale.com/careers)
4. [linkedin.com](https://www.linkedin.com/company/scaleai)
5. [greenhouse.io](https://job-boards.greenhouse.io/scaleai)

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