Applied AI Engineer - Enterprise Solutions

snorkelai; Deutschland; Hybrid; EUR 151.000 - 259.000; Vollzeit

Benefits dieser Stelle

Equity compensation

Hybrid work model

Travel up to 25%

Zusammenfassung

You will partner across product, engineering, and customer teams to scope use cases, develop robust deployments, and standardize reusable AI recipes. International travel up to 25% may be required.

Qualifikationen

• Bachelor's degree in a quantitative field or equivalent experience.
• Three or more years of customer-facing experience designing and implementing AI/ML solutions.
• Strong Python proficiency and solid software engineering fundamentals.
• Hands-on experience with modern Python tooling for type validation, typed data modeling, APIs, and ML orchestration.
• Broad expertise across the applied AI stack including LLMs, vectors, data processing, and evaluation tooling.
• Experience leading customer-facing initiatives across product, engineering, and business stakeholders.

Aufgaben

• Partner with enterprise customers to scope use cases and deploy Gen AI/ML solutions end to end.
• Build applied AI systems using retrieval-augmented generation, fine-tuning, prompts, and agent workflows.
• Design datasets and evaluation workflows ensuring reliability, transparency, and trust.
• Manage relationships with customer leadership across project lifecycles for successful deployments.
• Collaborate with pre-sales and product teams to map needs to capabilities and surface gaps.
• Standardize recurring solutions and contribute to internal tooling and enablement workshops.

Kenntnisse

Python programming

Software engineering fundamentals

ML system design

Project leadership

Ausbildung

Bachelor's degree in Computer Science, Engineering, Mathematics, or Statistics

Tools

ML orchestration

Vector/Embedding tooling

RAG tooling

LLM orchestration

Jobbeschreibung

Role overview

A customer-facing applied AI engineering role focused on designing and delivering generative AI and machine learning solutions for enterprise clients. The position bridges cutting-edge research with practical business outcomes, helping organizations build specialized AI systems that leverage their proprietary data for measurable impact.

Responsibilities

• Partner with enterprise customers to scope use cases, explore data, and develop and deploy Gen AI and ML solutions end to end.
• Build applied AI systems using techniques such as retrieval-augmented generation, fine-tuning pipelines, prompt engineering, and agentic workflows.
• Design augmented datasets and evaluation workflows that ensure model reliability, transparency, and stakeholder trust.
• Manage relationships with customer leadership and stakeholders across project lifecycles to drive successful deployments.
• Collaborate with pre-sales and product teams to map customer needs to existing capabilities and surface roadmap gaps.
• Standardize recurring solutions into reusable recipes, contribute to internal tooling, and lead enablement workshops for customer teams.

Requirements

• Bachelor's degree in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics, or equivalent experience.
• Three or more years of customer-facing experience designing and implementing AI/ML solutions.
• Strong proficiency in Python with solid software engineering fundamentals, including modular design, testing, profiling, and packaging.
• Hands-on experience with modern Python tooling for type validation, typed data modeling, type-safe systems, API frameworks, and ML orchestration.
• Broad expertise across the applied AI stack, spanning classical ML libraries, deep learning frameworks, foundation-model ecosystems, vector and embedding tooling, data processing frameworks, RAG tooling, and LLM orchestration and agent-authoring frameworks.
• Experience leading strategic, customer-facing initiatives and collaborating across product, engineering, and business stakeholders.

Nice to have

• Strong presentation skills with the ability to communicate clearly to both technical and executive audiences.
• Comfort working in a fast-paced environment and balancing priorities across multiple concurrent projects.

Benefits and work setup

• Hybrid work model based in San Francisco, CA or New York, NY.
• Equity compensation through employee stock options.
• Annual travel up to 25% for customer engagements.
• Salary range of $175,000 to $300,000 USD, depending on location and experience.