#Software Engineer

Qualcomm•San Diego, CA

5d•$99,500 - $149,300

About The Position

This position is not eligible for Qualcomm immigration sponsorship. We are seeking a highly motivated engineer to drive AI-powered engineering productivity initiatives across large-scale software development organizations. This role will focus on architecting and deploying agentic workflows, engineering automation platforms, software lifecycle optimization, and AI-assisted development solutions that improve engineering efficiency and product quality. The engineer will partner closely with engineering, program management, and AI platform teams to transform how software is built, validated, and maintained.

Requirements

Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

Nice To Haves

MS in Computer Science, Computer Engineering, or related field.
Strong proficiency in Python, C++, or comparable programming languages.
Experience building developer tools, automation systems, or engineering platforms.
Experience with large-scale software development environments.
Strong system design and architecture skills.
Excellent communication and cross-functional collaboration abilities.
Experience with Large Language Models (LLMs), AI agents, and RAG systems.
Experience building internal developer platforms.
Familiarity with Windows, embedded, mobile, or driver development environments.
Experience with telemetry, metrics, analytics, and engineering dashboards.
Experience deploying AI solutions into enterprise engineering workflows.
Knowledge of software quality, CI/CD, release engineering, and triage systems.

Responsibilities

Design and implement AI-powered engineering productivity solutions.
Develop and scale agentic workflow frameworks for engineering teams.
Build automation for software development lifecycle (SDLC) processes.
Create engineering dashboards, reporting systems, and operational metrics.
Enable AI-assisted debugging, triage, and root cause analysis workflows.
Collaborate with platform, tools, and product teams to identify high-value automation opportunities.
Define architecture and technical direction for engineering productivity services.
Drive adoption of generative AI technologies within software engineering workflows.
Partner with stakeholders to prioritize productivity investments based on measurable business impact.
Mentor engineers and provide technical leadership for strategic initiatives.