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Qualcomm

Senior Full‑Stack Developer

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

AI summarised

We are seeking a Senior Full-Stack Developer to support advanced engineering and analytics initiatives within a semiconductor product environment. The successful candidate will design and deliver scalable big-data analytic applications used across product, manufacturing, quality, and reliability engineering workflows. This role requires strong technical depth, excellent cross-team communication, and the ability to leverage modern AI tools to accelerate engineering productivity and drive efficient problem-solving.

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.

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.