Forward Deployed Engineer V, GenAI, Google Cloud

Google; Singapore; Remote; SGD 180,000 - 240,000; Full time

Job summary

Google Cloud’s Data Cloud team builds the data platform behind Google’s agentic AI offerings, including BigQuery, Managed Spark, Spanner, AlloyDB and Knowledge Catalog, integrated with Gemini Enterprise.

As a Forward Deployed Engineer, you’ll embed with customers to move data and ML workloads from idea to production on Google Cloud. You’ll leverage PySpark, SQL, Python and the data cloud ecosystem to build data foundations and train/evaluate models in real customer environments.

Qualifications

• Bachelor's degree in Engineering, Computer Science, or related field, or equivalent practical experience.
• 2 years of experience in software/data engineering, ML, or technical consulting, including Python/SQL.
• Experience with data cloud ecosystem products and cloud platforms (GCP).
• Experience building production-grade data cloud solutions from conception to launch, including pipelines.

Responsibilities

• Build production data and ML workloads with PySpark, SQL, and Python on BigQuery, Spark, Spanner, and AlloyDB.
• Stand up proofs with customer data and de-identify sensitive data.
• Build data foundations for agentic solutions, including lakehouse architectures and access controls.

Skills

Python

SQL

Data engineering

Cloud platforms

PySpark

Education

Bachelor's degree

Tools

BigQuery

Spanner

AlloyDB

Spark

Knowledge Catalog

Gemini

Job description

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

• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 2 years of experience in software engineering, data engineering, solution architecture, machine learning, or technical consulting, including experience writing code in Python and SQL.
• Experience with data cloud ecosystem products, technologies, or languages (e.g., Apache Spark, PySpark, BigQuery, Spanner, Knowledge Catalog, AlloyDB).
• Experience taking production-grade data cloud solutions from conception to launch, including architecting data systems on cloud platforms (e.g., Google Cloud Platform (GCP)) and building structured/unstructured pipelines.
• Experience training, evaluating, and deploying machine learning models in production.

Preferred qualifications:

• Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, Agent Development Kit (ADK)) and complex patterns (e.g., ReAct, self-reflection, hierarchical delegation).
• Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
• Experience in prompt developing, model evaluation, and the creative application of AI.
• Experience building applications on large language models over enterprise data (e.g., Gemini, agents, Retrieval-Augmented Generation (RAG), vector search) and evaluating them for quality, latency and cost.
• Experience migrating analytics, Spark or database workloads between platforms with measured cost or performance outcomes.

About the job

Google Cloud’s Data Cloud team builds the data platform behind Google’s agentic Artificial Intelligence (AI) offerings: BigQuery, Managed Spark, borderless Lakehouse, Spanner, AlloyDB and Knowledge Catalog, integrated with Gemini Enterprise.

About the job

Google Cloud’s Data Cloud team builds the data platform behind Google’s agentic Artificial Intelligence (AI) offerings: BigQuery, Managed Spark, borderless Lakehouse, Spanner, AlloyDB and Knowledge Catalog, integrated with Gemini Enterprise.

As a Forward Deployed Engineer (FDE) on our Data Cloud team, you will be an embedded builder who bridges the gap between frontier data solutions and production-grade reality for customers. You will function as an innovator-builder, working directly within customer's environments to move data and machine learning workloads from idea to production on Google Cloud, leveraging experience with programming languages (e.g., PySpark, SQL, Python) and the data cloud ecosystem (e.g., BigQuery, Managed Spark, Spanner, AlloyDB). You will build the data foundations that agents depend on, and train and evaluate machine learning models on customer data. You will serve a dual purpose: providing "white glove" deployment of complex systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap. It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.

Responsibilities

• Build and ship production data and machine learning workloads with customers, writing, testing, and performance-tuning PySpark, SQL and Python on BigQuery, Managed Spark, Spanner and AlloyDB.
• Stand up working proofs with customer's data, including de-identifying sensitive data (e.g., Payment Card Information (PCI), Protected Health Information (PHI)).
• Build the data foundation for agentic solutions, including lakehouse architectures, metadata and semantic context, and the access controls that let custom agents act on trusted data.
• Train, evaluate and deploy machine learning and agentic components where they improve the customer’s business metric, with evaluation and monitoring in place.
• Migrate high-cost analytics, Spark and operational database workloads from other platforms onto Google Cloud engines, with measured price-performance results.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.