Staff Applied AI Engineer - Enterprise AI Solutions

snorkelai; United States; Hybrid; USD 230,000 - 360,000; Full time

Benefits offered by this job

Equity included

Hybrid work model

On-target earnings range

Job summary

snorkel AI is seeking a Staff-level Applied AI Engineer to deliver generative AI and machine learning solutions for enterprise customers. The role bridges cutting-edge AI research with business outcomes, partnering with clients to scope use cases, build production systems, and translate recurring challenges into reusable internal tooling and best practices.

The role involves end-to-end collaboration with customers on GenAI/ML initiatives, designing AI systems (including retrieval-augmented

Qualifications

• 3+ years of customer-facing AI/ML design and delivery.
• Strong Python and production-grade software skills.
• Experience with retrieval, RAG, and LLM orchestration.
• Excellent communication with technical and executive audiences.

Responsibilities

• Partner with enterprise customers end-to-end on GenAI and ML initiatives.
• Design and implement AI systems (retrieval-augmented generation, fine-tuning pipelines, agentic workflows).
• Build augmented datasets and evaluation harnesses for reliability and trust.
• Cultivate relationships with customer leadership and technical stakeholders.
• Collaborate with pre-sales solutions and product teams to map needs to platform capabilities.
• Standardize solutions, contribute to internal tooling, and lead enablement workshops.

Skills

Python proficiency

Customer-facing

ML systems design

Stakeholder collaboration

Presentation skills

Education

Bachelor's degree

Job description

**Role overview**

Staff-level Applied AI Engineer focused on delivering generative AI and machine learning solutions to enterprise customers. The role bridges cutting-edge AI research with concrete business outcomes, partnering with clients to scope use cases, build production systems, and translate recurring challenges into reusable internal tooling, recipes, and best practices.

**Responsibilities**

• Partner with enterprise customers end-to-end on GenAI and ML initiatives, from use case discovery and data exploration through model development and deployment
• Design and implement modern AI systems such as retrieval-augmented generation, fine-tuning pipelines, prompt-engineering recipes, and agentic workflows
• Build augmented datasets and evaluation harnesses to support model reliability, transparency, and stakeholder trust
• Cultivate relationships with customer leadership and technical stakeholders to drive successful project delivery
• Collaborate with pre-sales solutions and product teams to map customer needs to platform capabilities and surface roadmap gaps
• Standardize solutions alongside other applied engineers, contribute to internal tooling, and lead enablement workshops for customers

Travel up to 25% annually

**Requirements**

• Bachelor's degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics, or equivalent practical experience
• 3+ years of customer-facing experience designing and implementing AI/ML solutions
• Strong Python proficiency with solid software engineering fundamentals (modular design, testing, profiling, packaging), including modern tooling for type validation, typed data modeling, testing, packaging, API services, serialization, and ML orchestration
• Deep expertise across the applied AI stack: classical ML libraries, deep learning frameworks, foundation-model ecosystems, vector/embedding stores, large-scale data processing, retrieval/RAG platforms, synthetic dataset curation, evaluation workflows, and LLM orchestration or agent-authoring frameworks
• Experience leading strategic customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions translate into measurable business outcomes
• Excellent presentation skills with both technical and executive audiences, plus the ability to juggle multiple projects in a fast-paced setting

Nice to have

• Hands-on experience with synthetic data generation, advanced evaluation design, and emerging agent-authoring patterns
• Track record of teaching or enablement work, including workshops and stakeholder education

Benefits and work setup

• Hybrid position based in San Francisco, CA or New York, NY
• On-target earnings of $230,000–$360,000 USD for Tier 1 (San Francisco Bay Area) locations, with equity included in offers; actual compensation varies by role, level, location, skills, and experience