Cloud Agentic AI Engineer

Quick Facts

• Role: Cloud Agentic AI Engineer

• Focus: Designing and deploying multi-step agentic AI solutions on Google Cloud for production environments

Description

You will design and implement multi-stage Agentic AI processes for client needs and bring AI/ML solutions into production. You’ll act as a technical advisor—analyzing client challenges, recommending solutions, and supporting implementation—while collaborating with customers, partners, and Google product teams.

Responsibilities

• Design and deploy multi-step Agentic AI workflows using ADK, Agent Engine, LangChain, and AgentSpace

• Build AI/ML solutions tailored to business requirements and implement them in production

• Provide technical advisory support to analyze client needs, recommend solutions, and help implement them

• Solve complex ML and AI integration problems

• Collaborate with clients, partners, and Google product teams during solution design and delivery

Requirements

• Minimum 7 years of practical experience in recommendation systems, data processing pipelines, or distributed ML

• Hands-on experience building multi-step Agentic AI processes using ADK, Agent Engine, LangChain, and AgentSpace (required)

• Broad experience in Machine Learning/AI and in technical consulting or delivering client solutions

• Strong knowledge of Vertex AI, MLOps, Document AI, and Generative AI

• Programming and scripting skills in Python, Perl, C, C++, or Java

• Understanding of the ML production lifecycle (feature engineering, data validation, monitoring, model management)

• Familiarity with ML tools/frameworks: TensorFlow, PyTorch, XGBoost

• Knowledge of data warehouse architectures and ETL/ELT, including analytics technologies: Apache Beam, Hadoop, Spark, Hive

• Ability to communicate complex technical topics and work with clients/partners

• Fluent English (verbal and written)

• Bachelor’s degree in a relevant field (CS, math, statistics, engineering) or equivalent practical experience

Benefits

• B2B collaboration

• Occasional customer travel (about 1–2 trips per few months)

• International environment with daily English communication

• Projects involving production deployments of Agentic AI and direct collaboration with customers, partners, and Google product teams

• Preferred start date: as soon as possible