- Страна
- США
- Зарплата
- 190 000 $ – 330 000 $
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Staff Applied AI Engineer - Pre-Sales
Высокая оценка обусловлена престижностью компании (выходцы из Stanford AI Lab), конкурентной зарплатой с опционами и возможностью работать на острие технологий GenAI. Роль предлагает отличный баланс между инженерией и стратегическим бизнесом.
Сложность вакансии
Роль требует редкого сочетания глубоких технических знаний в области GenAI (RAG, LLM, агенты) и выдающихся навыков продаж и коммуникации. Уровень Staff подразумевает высокую автономность и способность влиять на стратегию продукта через работу с клиентами.
Анализ зарплаты
Предлагаемый диапазон $190k - $330k OTE (включая бонусы за продажи) полностью соответствует и даже несколько превышает рыночные стандарты для позиций уровня Staff в области Applied AI в США, особенно с учетом опционов.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Applied AI Engineer (Pre-Sales) position at Snorkel AI. With over five years of experience in customer-facing technical roles and a deep background in both predictive ML and the modern GenAI stack, I have consistently demonstrated the ability to translate complex business challenges into high-impact technical solutions. My experience in leading technical discovery and developing bespoke RAG and LLM-based prototypes aligns perfectly with Snorkel's mission to transform expert knowledge into specialized AI.
Throughout my career, I have excelled at bridging the gap between technical engineering teams and executive stakeholders. I am particularly drawn to Snorkel AI because of its unique approach to data-centric AI development, which I believe is the most critical factor for production-ready systems today. I am eager to bring my expertise in Python, LLM orchestration, and solution scoping to help your prospects realize the full potential of the Snorkel platform and to contribute to your rapidly scaling team.
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Описание вакансии
About Snorkel
At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.
We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
About Snorkel
We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
As an Applied AI Engineer (Pre-Sales), you will partner closely with Sales and our AI Solution Practice Leaders during pre-sales engagements. You will lead technical discovery and solution scoping to identify high-value use cases, and develop tailored demos and pilots that demonstrate how modern GenAI and machine learning techniques can drive measurable business outcomes. You will also translate proposed solutions into clearly scoped, technically sound proposals and Statement of Works (SOWs) that set realistic expectations and position engagements for success, while collaborating with delivery teams during initial implementation.
This role sits at the intersection of deep technical problem-solving and customer partnership. You will help customers unpack complex business challenges, quickly prototype solutions, and clearly communicate technical approaches to both engineering teams and senior business stakeholders. From early architecture discussions to demo development, you will play a key role in helping organizations adopt AI effectively while surfacing field insights that inform our product and research roadmap.
Main Responsibilities
- Partner closely with Sales and our AI Solution Practice Leaders to shape technical strategy across active prospects, win technical evaluations, and ensure a seamless transition to post-sales delivery through structured handoff documentation and clear expectation alignment.
- Lead structured technical discovery engagements with prospects to understand business objectives, success criteria, data landscape, architectural constraints, security considerations, and organizational readiness.
- Translate discovery findings into well-defined GenAI solution architectures that demonstrate technical feasibility and business impact using internal frameworks, and complementary third-party technologies.
- Design, build and deliver bespoke demos, including evaluation pipelines, dataset strategy, retrieval-augmented generation systems, fine-tuning workflows, prompt engineering strategies, and agentic architectures tailored to specific customer use cases and senior business stakeholders.
- Author and contribute to custom proposals, including Statements of Work and RFP/RFI responses, ensuring scope clarity, architectural soundness, realistic effort estimates, and alignment with delivery capabilities.
- Systematically capture reusable patterns from bespoke demos and evolve them into reference architectures, demo assets, benchmarks, and internal solution playbooks.
- Annual travel up to 25%.
Preferred Qualifications
- B.S. in Computer Science, Engineering, Math/Statistics, or equivalent experience.
- 5+ years in customer-facing technical roles (pre-sales, solutions engineering, or applied AI), including discovery, scoping, demos, proof-of-value engagements, and RFP responses.
- Hands-on Python experience and familiarity with the modern Gen AI stack - LLM ecosystems, RAG, vector databases, data processing, synthetic dataset curation, evaluation workflows, LLM orchestration and agent authoring tools.
- Expertise across the predictive ML stack, including classical ML (e.g., scikit-learn) and data processing frameworks (e.g., pandas, Spark).
- Ability to operate in fast-paced environments and rapidly build prototypes (ML solutions, RAG systems, prompt-based workflows, fine-tuned models, agentic systems) that demonstrate business value.
- Able to translate ambiguous business problems into testable technical approaches and measurable success criteria.
- Strong presentation and storytelling skills with the ability to engage both technical and executive audiences with credibility.
- Experience estimating scope and producing technical content for proposals and Statements of Work.
Compensation range is $190K - $330K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Locations
New York; San Francisco Bay Area; Austin; Dallas; Seattle; Atlanta; Nashville; Boston; Remote - US
#LI-CG1
Salary Range
$190,000—$330,000 USD
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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Навыки
- Python
- Pandas
- Machine Learning
- Large Language Models
- Fine-tuning
- RAG
- Prompt Engineering
- Scikit-learn
- Spark
- Vector Databases
- Synthetic Data
Возможные вопросы на собеседовании
Проверка понимания специфики платформы Snorkel и умения объяснить ценность программной разметки данных.
Как бы вы объяснили техническому директору (CTO) крупного банка преимущество подхода Snorkel к программной разметке данных по сравнению с традиционной ручной разметкой?
Оценка практического опыта работы с современным стеком GenAI.
Опишите ваш опыт проектирования RAG-систем. С какими основными проблемами при масштабировании таких систем вы сталкивались и как их решали?
Проверка навыков пресейла и управления ожиданиями.
Как вы подходите к составлению Statement of Work (SOW) для проекта с высокой степенью неопределенности, например, при внедрении LLM-агентов?
Оценка способности быстро прототипировать решения.
Если у клиента есть специфический набор данных и задача по извлечению сущностей, какие шаги вы предпримете для создания работающего демо за 48 часов?
Проверка умения работать в связке с отделом продаж.
Расскажите о случае, когда технические требования клиента конфликтовали с текущими возможностями продукта. Как вы разрешили эту ситуацию в процессе пресейла?
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- Страна
- США
- Зарплата
- 190 000 $ – 330 000 $