GCP Engineer

Alldus; United States; On-site; USD 150,000 - 240,000; Full time

Job summary

Alldus is seeking a senior GCP Engineer to design and deliver enterprise cloud platforms enabling AI agents and complex integrations. You will drive production Vertex AI workloads, secure, scalable infrastructure, and collaborate with security and delivery teams to translate customer requirements into concrete cloud solutions.

The role emphasizes architecture design, tool integration, and reference patterns for enterprise customers, using Terraform, Config Connector, and GKE across multiple

Qualifications

• 8+ years of hands-on Google Cloud engineering experience
• Production experience with Vertex AI, Agent Builder, model deployment, prompt design, and tool calling
• Strong knowledge of compute, networking, storage, databases and messaging on GCP
• Terraform, Config Connector, and multi-project deployment architectures
• Strong Python skills for automation and integrations
• Experience with Kubernetes, GKE, Artifact Registry, and container security
• IAM, service accounts, workload identity federation, Cloud KMS and Org Policies
• REST APIs and gateway solutions using Apigee or API Gateway
• Cloud Logging, Monitoring, Trace, Git and CI/CD tooling
• On-premise integration with ERP systems
• English communication skills
• LangChain or Pydantic AI
• Vector databases and BigQuery analytics
• Regulated environments with security/audit/data residency
• OPA/Rego policy tooling
• ERP integrations with SAP/Oracle JD Edwards

Responsibilities

• Design and build production-ready AI agents using Vertex AI Agent Builder
• Integrate Gemini and Vertex AI models for flexible deployment
• Develop retrieval and knowledge solutions with Vertex AI Search, Vector Search, BigQuery
• Implement AI guardrails and secure data handling
• Design serverless, container-based, event-driven architectures (Cloud Run/Functions, GKE)
• Secure connections between GCP apps and enterprise systems (VPC, Private Service Connect)
• Develop reusable infrastructure with Terraform and Config Connector across projects/regions
• Implement IAM, workload identity federation, encryption, and data isolation
• Build CI/CD pipelines, infrastructure testing, monitoring, and release automation
• Collaborate with architects, security, and delivery teams to translate requirements
• Produce reference architectures, docs, and deployment patterns for customers

Skills

Google Cloud

Vertex AI

Python

Terraform

GKE / Kubernetes

Security & IAM

Education

Bachelor's degree in CS/Engineering

Tools

Terraform

Config Connector

GKE

Artifact Registry

BigQuery

Apigee / API Gateway

Job description

Alldus is hiring for a GCP Engineerto design and deliver enterprise cloud platforms that support AI agents and integrate with complex business systems. This is a senior technical opportunity for someone with deep Google Cloud expertise, production experience with Vertex AI, and the ability to build secure, scalable infrastructure for enterprise customers.

Key Responsibilities

• Design and build production-ready AI agents using Vertex AI Agent Builder, including tool calling, knowledge integration, orchestration, and evaluation.
• Integrate Gemini and other Vertex AI models, supporting flexible model selection and deployment.
• Develop retrieval and knowledge solutions using Vertex AI Search, Vector Search, Cloud SQL, AlloyDB, and BigQuery.
• Implement AI guardrails, content safety controls, and secure data handling.
• Design serverless, container-based, and event-driven architectures using Cloud Run, Cloud Functions, GKE, Workflows, Pub/Sub, Eventarc, and Cloud Tasks.
• Build secure connections between GCP applications and enterprise systems using VPC, Private Service Connect, and Cloud Interconnect.
• Develop reusable infrastructure using Terraform and Config Connector, supporting deployments across multiple projects and regions.
• Implement IAM, workload identity federation, encryption, and customer data isolation.
• Build CI/CD pipelines, infrastructure testing, monitoring, and release automation.
• Work with solution architects, security specialists, and delivery teams to translate customer requirements into practical cloud solutions.
• Produce reference architectures, technical documentation, and reusable deployment patterns, while supporting technical discussions with prospective customers.

Required Experience

• 8+ years of hands-on Google Cloud engineering experience, including at least three years in a senior engineering or architecture role supporting production enterprise workloads.
• Proven experience delivering AI/ML or agent-based workloads on GCP.
• Production experience with Vertex AI, Agent Builder, model deployment, prompt design, and tool calling.
• Strong knowledge of GCP compute, networking, storage, databases, and messaging services.
• Hands-on experience with Terraform, Config Connector, and multi-project deployment architectures.
• Strong Python skills for automation, tooling, and integrations.
• Experience with Kubernetes, GKE, Artifact Registry, and container security.
• Strong understanding of IAM, service accounts, workload identity federation, Cloud KMS, and Organization Policies.
• Experience designing REST APIs and gateway solutions using Apigee or API Gateway.
• Experience with Cloud Logging, Cloud Monitoring, Cloud Trace, Git, and CI/CD tooling.
• Experience connecting cloud applications to on-premise ERP systems, databases, or legacy middleware.
• Strong communication skills and fluency in written and spoken English.
• Agent frameworks such as LangChain or Pydantic AI.
• Vector databases, retrieval architectures, and BigQuery analytical workloads.
• Regulated environments with strict security, audit, and data residency requirements.
• Assured Workloads, sovereign cloud deployments, or policy-as-code using OPA/Rego.
• Java application integration and enterprise ERP platforms such as SAP, Oracle EBS, or JD Edwards.
• Google Cloud Professional certifications in Architecture, DevOps, Machine Learning, or Security.
• A degree in Computer Science, Engineering, or a related discipline.