Forward Deployed Engineer, GenAI, Google Cloud, Data

the company will be prioritizing applicants who have a current right to work in Singapore, and do not require the company's sponsorship of a visa.

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 8 years of experience with software development and data engineering with SQL, Python, Java, Scala, or Go.
• Experience with modern Extract, Transform, Load/Extract, Load, Transform (ETL/ELT) frameworks (e.g., dbt, Dataform) and designing enterprise data modeling layers or data marts.

• Master's degree or PhD in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
• Experience integrating semantic metadata formats enterprise taxonomies, or ontologies into large-scale data warehouses and lakes.
• Deep experience designing batch, offline, and online evaluation harnesses and intelligence mining jobs to benchmark LLM capabilities (e.g., Text-to-SQL accuracy, semantic parsing, etc).
• Practical knowledge of configuring and deploying secure code execution harnesses and interpreter sandboxes (e.g., Python/SQL execution environments) for automated data analysis.
• Advanced expertise in synthetic data generation at scale while maintaining multi-table referential integrity using tools like Faker, Snowfakery, or custom constraint engines.

We build frontier models and foundational data platforms.

As a Forward Deployed Engineers (Data and AI) you will work seamlessly over massive, complex enterprise data lakes, warehouses, and transactional systems in production, under real latency, throughput, and governance constraints. You will embed with the engineering and data architecture organizations of the largest customers to take the company's enterprise data and AI stack BigQuery, Dataproc, Dataflow, Dataform/dbt, Gemini for Data, and code execution sandboxes, from architectural whiteboard to high-throughput, production-grade workflows. You will identify what slows a 25,000-engineer enterprise down when deploying Text-to-SQL, automated evaluations, and data intelligence workflows, design the data systems that fix it, and own them end-to-end: discovery, pipeline engineering, semantic data modeling, evaluation harness setup, rollout, and long-tail reliability.

• Serve as a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows that drive measurable Return on Investment (ROI).
• Co-build with customer engineering teams to instill the company-grade development best practices, ensuring long-term project success and high end-user adoption.
• Design and build high-throughput batch and streaming data pipelines and utilities to curate multi-terabyte evaluation datasets and execute offline/online evaluation generation jobs for model intelligence mining.
• Construct scalable ETL/ELT pipelines using Dataform, dbt, BigQuery, or Dataproc to design enterprise data marts and semantic modeling layers specifically engineered to maximize data quality, schema clarity, and accuracy for Text-to-SQL and natural language analytical interfaces.
• Create mechanisms for large-scale synthetic data generation that maintain strict referential integrity across complex relational schemas, leveraging advanced tools and custom generative utilities for privacy-safe model benchmarking and fine-tuning.

the company is proud to be an equal opportunity workplace and is an affirmative action employer.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

See also the company's EEO Policy and EEO is the Law.

If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.