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Qualcomm

Senior Full‑Stack Developer

Qualcomm
Fabless SemiconductorSingapore, Central Singapore, SingaporeOnsitePosted 2 days ago
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About the role

AI summarised

This Senior Full-Stack Developer role involves designing and architecting scalable big-data analytics systems within a semiconductor product environment. The position focuses on building backend microservices and intuitive front-end dashboards to support manufacturing, yield, and quality engineering workflows using AI-driven tools.

FablessOnsite

Key Responsibilities

  • Architect, design, and develop full‑stack systems for high‑volume data and analytics applications supporting semiconductor product and operations teams
  • Build robust backend services, microservices, and APIs to enable secure, scalable processing of engineering and manufacturing datasets
  • Develop user‑centric and intuitive front‑end interfaces for data visualization, yield/quality dashboards, and analytic workflows
  • Design and optimize data models across SQL and NoSQL platforms used for device, product, and test data
  • Collaborate closely with cross‑functional partners including product and test engineering and IT team
  • Use AI/LLM‑based tools for code acceleration, documentation, data analysis, and engineering‑vibe synthesis
  • Provide clear communication of design decisions, tradeoffs, and architectural recommendations to technical and non‑technical stakeholders
  • Contribute to agentic AI application design, including autonomous data processing agents, agent workflows, or LLM‑tool integrations

Requirements

  • 7–10 years of professional full‑stack development experience
  • Strong backend expertise in one or more of Node.js, Python
  • Proficiency in modern front‑end frameworks (React, Angular)
  • Strong foundational understanding of big‑data system architecture, distributed computing, and data pipelines
  • Hands‑on experience with SQL databases (PostgreSQL, MySQL, MS SQL) and NoSQL systems (MongoDB, DynamoDB, Redis)
  • Experience deploying systems on cloud environments (Azure, AWS, or GCP)
  • Excellent communication skills with ability to explain complex concepts to engineers, managers, and cross‑functional teams
  • Demonstrated use of AI tools to enhance software engineering output, analytics velocity, or workflow automation
  • Experience designing agentic AI systems or LLM‑integrated applications
  • Familiarity with semiconductor engineering data (yield, parametric, test logs, product data, reliability data)
  • Experience with Kafka, RabbitMQ, or other event-driven systems
  • Strong system design, architecture, and documentation skills