Full Stack AI Engineer - Product Deployment (Python and React )

Role & responsibilities

Full-Stack AI Engineer - Product Deployment

About the Role

We're looking for a full-stack AI engineer who can independently take an Agentic AI platform from codebase to a fully working, client-facing deployment. This is a hands-on build-and-ship role you will write frontend code, build backend APIs, integrate with the client's SAP or Oracle systems, and stand up the data lake that powers platform 's agents. You should be comfortable owning a client environment end-to-end rather than working on one layer of the stack.

Key Responsibilities

• Build & enhance the frontend: Develop and maintain the platform web application (React/TypeScript) — dashboards, chat interfaces, and agent output screens.
• Build & enhance the backend: Develop and maintain APIs (Python/FastAPI or Node.js) powering platform 's Agents and related services.
• Own SAP/Oracle integration: Build and configure connectors into the client's ERP (SAP OData/BTP CPI or Oracle OIC) to extract PO, vendor, contract, and material master data on a governed, non-agentic pipeline.
• Stand up the data lake: Provision and configure BigQuery/Synapse, vector stores, and document stores; build ETL pipelines to cleanse and ingest historical spend, drawing, and contract data.
• Deploy agents in the client environment: Configure and deploy AI agents (Gemini/Vertex AI or Azure OpenAI) with prompt engineering, RAG pipelines, and orchestration logic specific to the client's category structure.
• Own the full deployment lifecycle: Take a use case from requirements through data integration, agent build, testing, and go-live — coordinating directly with client IT and procurement stakeholders.
• Troubleshoot production issues: Debug and resolve issues across the full stack post-deployment, including data pipeline failures, agent output quality issues, and integration errors.