Appen 2 Forward Deployed Engineer at Appen 2 responsible for designing, deploying, and optimizing GenAI data solutions with ownership of data quality. Works closely with clients and engineering to deliver scalable workflows and datasets.
Responsibilities
Act as a trusted consultative partner to clients by defining requirements, clarifying success criteria, shaping high-quality annotation guidelines, and proactively providing insights.
Influence the what and the why behind GenAI data solutions by translating ambiguous client needs into clear, scalable workflows.
Deliver GenAI datasets that meet all defined acceptance and quality criteria.
Define the validation and automation requirements that reduce variance, manual review effort, rework, and time to validation.
Partner with engineering to build requirements as scalable, reproducible, and observable pipelines.
Contribute reusable quality frameworks and validators adopted across multiple projects.
3+ years of experience in a customer-facing technical role such as solutions engineering, solutions architect, data or technical consulting, or data operations.
Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, or a related field, or equivalent practical experience.
Experience working on GenAI, machine learning, or model evaluation data, including LLM training, annotation, or evaluation workflows.
A consultative problem-solving approach when leading client conversations, asking sharp questions, and guiding stakeholders toward better decisions.
Ability to vibe code but proficiency in Python and SQL is a plus
Confidence in working directly with client engineering or machine learning teams.
Qualification
Bachelor's degree in Computer ScienceExperience working on GenAI
Required
3+ years experience in customer-facing technical role such as solutions engineering, solutions architect, data or technical consulting, or data operations
Bachelor's degree in Computer Science, Engineering, Data Science, Statistics, or related field, or equivalent practical experience
Experience working on GenAI, machine learning, or model evaluation data including LLM training, annotation, or evaluation workflows
Consultative problem-solving approach in client conversations
Confidence working directly with client engineering or machine learning teams
