Applied AI Engineer - Pre-Sales

Snorkel AI is on a mission to democratize AI by building the definitive AI data development platform. As an Applied AI Engineer (Pre-Sales), you will partner with Sales and AI Solution Practice Leaders to lead technical discovery and solution scoping, develop tailored demos, and help customers adopt AI effectively while ensuring a smooth transition to post-sales delivery.

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%

Requirements:

• 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