Client‑Facing GenAI Data Solutions Engineer

Praxy; San Francisco (CA); Hybrid; USD 140,000 - 180,000; Full time

Benefits offered by this job

health insurance

professional development

Job summary

Appen is seeking a Forward Deployed Engineer in San Francisco to design, deploy, and optimize GenAI data solutions with ownership of data quality. You will work across engineering, data operations, and client delivery, ensuring datasets, pipelines, and automations meet accuracy and performance criteria for GenAI model development.

You will engage with clients to define requirements, translate needs into scalable workflows, and deliver datasets that meet acceptance criteria.

Qualifications

• 3+ years in a customer-facing technical role such as solutions engineering, solutions architect, data or technical consulting, or data operations.
• Experience with GenAI, machine learning, or model evaluation data (LLM training, annotation, or evaluation workflows).
• Consultative problem-solving approach guiding stakeholder decisions.

Responsibilities

• Define requirements and success criteria for client projects.
• 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 manual review and rework.
• Collaborate with engineering to build scalable, observable pipelines.
• Contribute reusable quality frameworks used across projects.

Skills

Customer-facing experience

GenAI/ML exposure

Python, SQL (plus)

Education

Bachelor's degree in CS/Engineering/Data Science/Statistics

Job description

Appen is seeking a Forward Deployed Engineer in San Francisco to design, deploy, and optimize GenAI data solutions with ownership of data quality. You will work across engineering, data operations, and client delivery, ensuring datasets, pipelines, and automations meet accuracy and performance criteria for GenAI model development.

You will engage with clients to define requirements, translate needs into scalable workflows, and deliver datasets that meet acceptance criteria.