Forward Deployed Engineer V, GenAI, Google Cloud - Singapore

Google Inc.; Singapore; Presencial; SGD 120.000 - 170.000; Jornada completa

Descripción de la vacante

Google Cloud is seeking a Forward Deployed Engineer for its Data Cloud team in Singapore. You will act as an embedded builder, moving data and ML workloads from idea to production within customer environments using PySpark, SQL, Python and Google Cloud tools such as BigQuery, Spanner, and AlloyDB.

You will de-identify sensitive data, build lakehouse architectures, and deploy ML components aimed at improving client metrics, while migrating analytics workloads and contributing to product roadmap

Formación

• Bachelor’s degree in Engineering/CS or equivalent practical experience.
• 2 years of software/data engineering, ML, or related consulting.
• Experience with Python and SQL development and data cloud ecosystems.
• Experience taking cloud data solutions from conception to production.
• Experience training and deploying ML models in production.

Responsabilidades

• Build and ship production data and ML workloads with PySpark, SQL, Python on Google Cloud.
• Stand up proofs with customer data, including de-identification of PCI/PHI.
• Build data foundations for agentic solutions with lakehouse architectures and access controls.
• Train, evaluate, and deploy ML components to improve business metrics.
• Migrate analytics workloads to Google Cloud with cost-performance gains.

Conocimientos

Python

SQL

PySpark

BigQuery

Spanner

AlloyDB

Knowledge Catalog

Apache Spark

Educación

Bachelor's degree

Herramientas

LangGraph

CrewAI

ADK

Descripción del empleo

Product area

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.

Job description

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.

Job 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.

Minimum qualifications

• 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.