IE4 - AI Google Cloud Platform
Irving, Texas, United States of America
Contract
2 weeks ago
$68 USD
Key skills
PythonAILangChainAgenticFastAPIFlaskGoogle CloudTerraformGKEHelmIAMSageMakerBedrockVertex AIGitCI/CDLeadershipCommunicationFirewall
About this role
Outstanding long-term contract opportunity! A well-known Financial Services Company is looking for a Google Cloud Platform AI Engineer in Charlotte, NC (Hybrid).
Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.
Google Cloud Systems Operations Engineer and Automation/Agentic AI Developer Focus
In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering.
Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Provide expertise to client senior leadership on innovative Engineering business solutions. Strategically engage with client personnel.
Required Qualifications: 9+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Advanced Google Cloud Engineering & Operations (4 to 6 years) Deep expertise building and operating Google Cloud Platform environments: Compute Engine, VPC Networking, Load Balancers, Storage, IAM, Monitoring.
Python Development and Google Cloud Platform API Automation (> 5 years) Strong production quality Python development/engineering skills.
Agentic AI Development for Google Cloud Platform Operations (> 3 years) Experience developing agentic AI workflows for Google Cloud Platform operational tasks and remediation.
API Automation Platform (FastAPI / Flask) Ability to build, extend, and maintain a Python based automation platform (FastAPI or Flask).
This is an excellent opportunity for a detail-oriented Google Cloud Platform AI Engineer to contribute to a high-impact team in a hybrid remote environment.
Work with the brightest minds at one of the largest financial institutions in the world. This is a long-term contract opportunity that includes a competitive benefit package! Our client has been around for over 150 years and is continuously innovating in today's digital age. If you want to work for a company that is not only a household name, but also truly cares about satisfying customers' financial needs and helping people succeed financially, apply today.
Google Cloud Systems Operations Engineer and Automation/Agentic AI Developer Focus
In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Engineering.
Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. Provide expertise to client senior leadership on innovative Engineering business solutions. Strategically engage with client personnel.
Required Qualifications: 9+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Advanced Google Cloud Engineering & Operations (4 to 6 years) Deep expertise building and operating Google Cloud Platform environments: Compute Engine, VPC Networking, Load Balancers, Storage, IAM, Monitoring.
- Experience diagnosing, debugging, remediation, upgrades, patching, and RCA across Google Cloud Platform resources.
- Strong experience with GKE, Big Data Platforms, Cloud Armor, Configuration/patching, Terraform, VNETs, NSGs, App Gateways, Firewall/Load Balancers, Managed Identities, Policies, and Logs/Monitoring/Alerts.
Python Development and Google Cloud Platform API Automation (> 5 years) Strong production quality Python development/engineering skills.
- Hands on experience with Google Cloud SDK and MCP Servers for Python and automation across Compute, Network, Storage, IAM.
- Ability to build automated remediation workflows and operational tooling in Python and ability to add MCP tools/skills to manage the Google Cloud (Google Cloud Platform) operations.
- High code quality: Unit Tests, Vulnerability Management.
- Packaging & deployment experience: Helm/Containers (if used), CI/CD pipelines, Git workflows.
- System engineering experience and strong technical communication and documentation skills.
Agentic AI Development for Google Cloud Platform Operations (> 3 years) Experience developing agentic AI workflows for Google Cloud Platform operational tasks and remediation.
- Strong skills with LangChain, MCP server, A2A, Google ADK/Agents, or similar multi agent frameworks.
- Ability to develop tools/skills that allow agents to safely execute Google Cloud Platform operational actions.
- Ability to build tool calling agents using Google Cloud Platform APIs safely and deterministically.
- Experience building self-hosted, Python based agentic systems (no Vertex AI, SageMaker, Bedrock, or managed AI platforms).
API Automation Platform (FastAPI / Flask) Ability to build, extend, and maintain a Python based automation platform (FastAPI or Flask).
- Experience designing AI driven operational endpoints and tooling layers for Google Cloud Platform.
This is an excellent opportunity for a detail-oriented Google Cloud Platform AI Engineer to contribute to a high-impact team in a hybrid remote environment.