GenAI Data Solutions Engineer (Client-Facing)

Appen 2; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Appen seeks a Forward Deployed Engineer to design, deploy, and optimize GenAI data solutions with enterprise clients, owning data quality across datasets, pipelines, and automations. This hybrid role in San Francisco requires collaboration with client teams and engineering to deliver scalable workflows with a focus on accuracy, reliability, and performance.

You will translate client needs into concrete requirements and guide stakeholders toward better decisions through hands-on technical

Qualifications

• 3+ years in a customer-facing technical role such as solutions engineering, data consulting, or data operations.
• Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, or related field, or equivalent practical experience.
• Experience with GenAI, ML, or model evaluation data (LLM training, annotation, evaluation workflows).
• Consultative problem-solving approach guiding stakeholders to better decisions.
• Proficiency in Python and SQL is a plus.
• Ability to work directly with client engineering or ML teams.

Responsibilities

• Act as a trusted consultative partner to clients by defining requirements, clarifying success criteria, shaping high-quality annotation guidelines, and proactively providing insights.
• Translate ambiguous client needs into clear, scalable GenAI data workflows.
• Deliver GenAI datasets meeting defined acceptance and quality criteria.
• Define validation and automation requirements to reduce variance and rework.
• Partner with engineering to build scalable, reproducible pipelines.
• Contribute reusable quality frameworks and validators adopted across projects.

Skills

Customer-facing

GenAI experience

Python

SQL

Client collaboration

Education

Bachelor's degree in CS/Engineering/Data Science

Job description

Appen seeks a Forward Deployed Engineer to design, deploy, and optimize GenAI data solutions with enterprise clients, owning data quality across datasets, pipelines, and automations. This hybrid role in San Francisco requires collaboration with client teams and engineering to deliver scalable workflows with a focus on accuracy, reliability, and performance.

You will translate client needs into concrete requirements and guide stakeholders toward better decisions through hands-on technical