Full Stack Engineer (AI/Python/React)

PERSOL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 110,000 - 160,000; Full time

Job summary

PERSOL SINGAPORE PTE. LTD. is seeking a Full Stack Engineer to design and deliver AI-enabled HR applications on Microsoft Azure.

You will develop backend services in Python with FastAPI, frontend in React/TypeScript, and manage data in SQL within Fabric, delivering secure, scalable features across UI, API, and database. Collaborate with the Technical Lead, AI Engineer, UI/UX Engineer and Product Owner to create conversational workflows, handle approvals, and ensure robust testing, deployment,

Qualifications

• At least 4 years of professional software development experience.
• Experience building AI-enabled apps on Azure with Python backend and React frontend.
• Strong SQL and relational database design, including Azure SQL or SQL Server.
• Experience with REST APIs, async programming and CI/CD pipelines.
• Knowledge of securing apps with OAuth 2.0/OpenID Connect and tenant isolation.

Responsibilities

• Develop Python/FastAPI backends with clear contracts and validation.
• Build frontend in React/TypeScript for employee self-service and dashboards.
• Integrate AI services via Azure OpenAI, RAG and agent tools with proper approvals.
• Design and optimize SQL databases and data access across Fabric and OneLake.
• Ensure secure deployment on Azure with monitoring, logging and rollback capabilities.

Skills

Python

FastAPI

React

TypeScript

Azure

SQL

Docker

Git

CI/CD

APIs

Education

Degree or Diploma in Computer Science or related field

Tools

SQL Server

Azure SQL

Microsoft Fabric

OneLake

Power BI

API Gateway

Job description

12 Months Contract
Working Location: Central
Monday - Friday, 9am to 6pm

Overview

We are seeking a Full Stack Engineer with practical experience building and deploying AI-enabled applications on Microsoft Azure. You will develop UCore AI HR using Python and FastAPI for backend services and the API gateway, React and TypeScript for the frontend, and SQL database in Microsoft Fabric for operational data.

You will turn HR requirements into secure, tested features that work across the user interface, APIs and database. Working with the Technical Lead, AI Engineer, UI/UX Engineer and Product Owner, you will deliver conversational workflows that let users complete HR tasks through voice, text and interactive dashboards, with appropriate validation and human approval.

Responsibilities

Frontend and conversational experience

• Build responsive React and TypeScript interfaces for employee self-service, HR operations, manager dashboards and administration, including accessible mobile and PWA experiences.
• Integrate chat, voice and avatar components with business workflows. Implement streaming responses using SSE or WebSocket, including loading, cancellation, error recovery and clear transaction status.
• Develop a reusable React component registry. Validate AI-generated UI instructions against approved schemas and components so that dynamic dashboards remain predictable and secure.

Python services and API gateway

• Develop Python/FastAPI APIs with clear contracts, validation, versioning, asynchronous processing and reliable error handling. Maintain automated API documentation.
• Keep the Python gateway focused on token validation, trusted tenant context, routing, rate limiting, correlation IDs, streaming and request aggregation. Implement HR rules and AI orchestration in their respective services.
• Build assigned HR workflows across Core HR, headcount, recruitment, onboarding, leave, attendance, claims and payroll. Implement approval states, audit records and repeat-safe transaction handling.

Platform delivery responsibilities

AI integration and controlled execution

• Work with the AI Engineer to connect Azure OpenAI/OpenAI services, agent tools and retrieval-augmented generation (RAG) to authorised application APIs. Support conversation context, structured responses and source references.
• Enforce permissions, tenant boundaries, input validation and required approvals before executing AI-proposed actions. Provide review and confirmation steps for sensitive changes and protect against duplicate execution.
• Instrument AI request latency, failures and usage. Implement agreed limits, timeout handling and fallback behaviour, and help diagnose failures across the UI, gateway and AI services.

Data and shared platform services

• Design relational schemas, migrations, indexes and data-access code for SQL database in Microsoft Fabric. Implement transactions, concurrency controls, data validation and query optimisation.
• Work with data specialists to connect operational data to OneLake, Lakehouse, Warehouse, semantic models and Power BI. Maintain clear boundaries between transactional processing and analytical reporting.
• Develop tenant provisioning, workflow, notifications, document handling and audit capabilities. Apply subscription, module, seat and usage entitlements on the server, keeping commercial access controls separate from feature rollout.
• Build secure third-party integrations, including HR, payroll and bank APIs where assigned. Handle credentials, retries, idempotency, reconciliation and traceable failure recovery.

Azure deployment and application security

• Containerise and deploy applications using the selected Azure runtime, such as Azure Container Apps or App Service. Maintain repeatable environment configuration, CI/CD pipelines and infrastructure as code.
• Integrate with Azure Front Door, WAF, API Management and Microsoft Entra ID/External ID. Apply role-based access, least-privilege permissions, managed identities, secure secret storage and protection of personal data.
• Support deployment in customer Azure environments, tenant isolation, controlled releases and rollback. Monitor application health with Azure Monitor/Application Insights and investigate production incidents.

Engineering quality and collaboration

• Write meaningful unit, integration and end-to-end tests, including permission and tenant-isolation checks. Support UAT, defect resolution, performance testing and release readiness.
• Review existing services and refactor them incrementally with regression protection. Document technical decisions, deployment steps and support procedures; review code and guide junior engineers or interns.

Requirements

• Degree or diploma in Computer Science, Software Engineering or a related discipline, or equivalent practical development experience.
• At least 4 years of professional software development experience, including substantial hands‑on delivery of Python backend services and React applications.
• At least 2 years of practical Azure application development and deployment experience, with responsibility for production releases, monitoring and troubleshooting.
• Strong Python, FastAPI, REST API design and asynchronous programming skills, together with React, TypeScript, frontend state management and API integration.
• Experience delivering at least one AI-enabled application beyond a demonstration, including LLM API integration and practical handling of errors, access controls, latency and usage costs.
• Strong SQL and relational database skills, including schema design, transactions, indexing, migrations and secure application access. Experience with SQL Server, Azure SQL or SQL database in Microsoft Fabric is relevant.
• Practical knowledge of OAuth 2.0/OpenID Connect, token validation, role-based permissions and tenant isolation. Comfortable using Docker, Git, automated tests and CI/CD pipelines.
• Ability to estimate and deliver features, investigate issues across application layers, explain technical trade-offs and collaborate with product, design and AI colleagues.

Preferred experience

• Direct experience with SQL database in Microsoft Fabric, OneLake and Power BI integration.
• RAG, vector search, agent tool integration, speech services or real‑time conversational interfaces.
• Enterprise SaaS, HR/payroll applications, approval workflows, licensing and usage metering, or secure banking integrations.
• C#/.NET code comprehension and incremental migration or integration of existing services with Python.
• Infrastructure as code using Bicep or Terraform, customer-hosted Azure deployments, or relevant Microsoft Azure certification.