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Snorkel AI

Builds training data and test environments for AI

Staff Applied AI Engineer - Pre-Sales

Pre-Sales Solution EngineeringPosted on Nov 11
Full-time$190k - $330k

About the Job

Requirements

  • Preferred: A B.S. in Computer Science, Engineering, Math/Statistics, or equivalent experience.
  • Preferred: 8+ years in customer-facing technical roles such as pre-sales, solutions engineering, or applied AI, including discovery, scoping, demos, proof-of-value engagements, and RFP responses.
  • Preferred: Hands-on Python experience and familiarity with modern generative AI tools and techniques, including large language model ecosystems, retrieval-augmented generation, vector databases, data processing, synthetic dataset curation, evaluation workflows, large language model orchestration, and agent authoring tools.
  • Preferred: Expertise across the predictive machine learning stack, including classical machine learning such as scikit-learn and data processing frameworks such as pandas and Spark.
  • Preferred: Ability to rapidly build prototypes, including machine learning solutions, retrieval-augmented generation systems, prompt-based workflows, fine-tuned models, and agentic systems, to demonstrate business value.
  • Preferred: Ability to translate ambiguous business problems into testable technical approaches and measurable success criteria.
  • Preferred: Strong presentation and storytelling skills to engage technical and executive audiences credibly.
  • Preferred: Experience estimating scope and producing technical content for proposals and Statements of Work.

Responsibilities

  • Partner with Sales and AI Solution Practice Leaders to shape technical strategy across active prospects, win technical evaluations, and ensure 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 generative AI 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 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.
  • Capture reusable patterns from bespoke demos and evolve them into reference architectures, demo assets, benchmarks, and internal solution playbooks.
  • Travel up to 25% annually.

About the Company

Snorkel AI

Builds training data and test environments for AI

Snorkel AI builds training datasets and simulated work environments for AI labs and companies developing models and software agents. Its data products combine expert demonstrations, scoring rules, and quality checks, while runnable environments let agents practice tasks such as coding or using business software. The company pairs domain specialists with its own data development technology to generate examples, evaluate model behavior, and refine weak areas through repeated feedback. Customers buy ready-made datasets or commission tailored data and evaluation work, and enterprises also use its specialized agent solutions. Snorkel AI was founded in 2019 and is headquartered in San Francisco, California.

Company size
201-500
Company stage
Late Stage VC
Total funding
$586.2M
Headquarters
San Francisco, CA
Founded
2019

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