** Note: No relocation assistance or visa sponsorship is available for this position. **

Number of Position(s): 1

Duration: 4 months

Dates: January 2027 - May 2027, full-time

Location: Onsite in Sunnyvale, CA

EDUCATIONAL RECOMMENDATIONS:

Currently a candidate pursing a bachelor's degree or master's degree in Computer Science, Software Engineering, Artificial Intelligence or a related field with an accredited school in the United States.

Develop and enhance AI workflows, features, and services under the guidance of senior engineers.
Implement AI-assisted software development capabilities, including agent workflows, code generation, testing, and documentation automation.
Support the development of reusable templates, frameworks, and best practices for Agentic PDLC, AI-SDLC, B-MAD, and modern software engineering processes.
Develop integrations with development toolchains, CI/CD systems, repositories, issue management platforms, and AI services.
Build and maintain automation for requirements management, design reviews, coding, testing, security scanning, and release readiness verification.
Create dashboards, metrics, and reporting capabilities to measure engineering productivity and AI adoption.
Develop and maintain technical documentation, tutorials, onboarding materials, and knowledge assets.
Participate in sprint planning, backlog refinement, implementation, testing, and code reviews.
Support proof-of-concept initiatives evaluating emerging AI engineering technologies and autonomous development workflows.
Collaborate with product, support, SRE, and development teams to identify and implement productivity improvements.
Demonstrate flexibility to collaborate across time zones as needed to support business requirements.

Basic programming skills in Python and Go, with experience applying software development practices through academic coursework, internships, research, or personal projects.
Interest in Generative AI, AI agents, large language models (LLMs), automation, and modern software engineering methodologies, including B-MAD, Loop Engineering, and AI-PDLC/AI-SDLC frameworks.
Familiarity with cloud-native technologies, Linux environments, Git-based version control, and container platforms such as Docker and Kubernetes is preferred.
Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively in a diverse, global team environment.

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