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Full Stack Engineer
Job description
An enterprise client is seeking a highly skilled Full Stack Engineer for a high-velocity contract engagement. In this role, you will be responsible for building and deploying a modern, AI-integrated application hosted entirely on Google Cloud Platform (GCP). You will own the end-to-end development cycle, bridging a responsive React/TypeScript frontend with a high-performance Python/FastAPI backend.
A core component of this project involves integrating Google's Vertex AI (Gemini models) to drive intelligent data extraction and risk assessment features. Frontend Development: Design and build robust, highly responsive user interfaces using React and TypeScript. Backend & API Development: Architect and develop scalable backend services and RESTful APIs using Python and the FastAPI framework.
Cloud-Native Deployment: Containerize and deploy frontend and backend services utilizing serverless GCP Cloud Run. Data Pipelining: Design, deploy, and manage asynchronous data processing pipelines using Cloud Run Jobs. AI/ML Integration: Connect the application to Google's foundation models (Gemini) via Vertex AI to execute complex data extraction and automated risk assessments.
Database Management: Utilize Firestore for real-time application state management and metadata storage, while integrating Big. Query for heavy data warehousing and analytics workloads. Security & Authentication: Implement enterprise-grade Single Sign-On (SSO) by configuring Google's Identity-Aware Proxy (IAP) and integrating it with Microsoft Entra ID.
DevOps & CI/CD: Maintain and optimize deployment workflows using Azure DevOps to ensure seamless CI/CD pipelines into the GCP environment. To be successful in this project, candidates must be able to hit the ground running with the following technologies: Frontend: Deep proficiency in React and TypeScript. Backend: Strong Python programming skills with hands-on FastAPI experience.
GCP Ecosystem: Proven experience with Google Cloud serverless architecture, specifically Cloud Run and Cloud Run Jobs. Databases: Experience structuring document databases (Firestore) and querying analytical data warehouses (Big. Query). AI/LLMs: Practical experience integrating LLMs or GenAI APIs into production applications (Vertex AI / Gemini preferred).
Identity & Access: Familiarity with enterprise SSO, Microsoft Entra ID (formerly Azure AD), and GCP Identity-Aware Proxy (IAP). DevOps: Experience configuring and troubleshooting CI/CD pipelines in Azure DevOps targeting Google Cloud. Ideal Candidate Profile Self-Starter: You thrive in fast-paced contract environments and can rapidly familiarize yourself with an existing architecture.
Full-Stack Mindset: You are equally comfortable debugging a React state issue as you are optimizing a Python API or writing a Big. Query SQL statement. Quality Focused: You write clean, well-documented, and maintainable code with a strong understanding of cloud security best practices. Only applicants located in UK may apply.
Fully remote opportunity.
Description copied from Lifted, an Upwork Company's careers page. Read the full posting before you apply.
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