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Google Software Engineer Internship Jobs in Oregon

About the Role The Revenue Cycle Management (RCM) team is seeking a Staff Software Engineer to lead ... Leverage experience with cloud platforms (AWS, Azure, Google Cloud, etc.) to design cloud-native ...

Staff Software Engineer - Scala

OR · On-site +1

$150K - $200K/yr

We are seeking a highly skilled and experienced Staff Software Engineer to join our Trading ... Experience with Kubernetes and cloud services (e.g., Google Cloud Platform), with a focus on ...

OR

$190K - $250K/yr

Senior Software Engineer, Applications AcuityMD is a software and data platform that accelerates ... google cloud services, or equivalent technologies * Curious mind and enjoy learning about and ...

OR

$122K - $161K/yr

Senior Staff Software Engineer - Identity & Access Management PlatformWhy Kaseya? Join a fast ... Experience integrating enterprise identity providers such as Microsoft Entra ID, Okta, Google ...

OR

$122K - $161K/yr

Deep proficiency in Google Cloud Platform (GCP) is required; AWS experience is a strong plus. You ... Software Engineering & DevEx * Coding Proficiency: Strong software development skills in high-level ...

As a Software Engineer on the Distribution Platform team at Upstart, you will be instrumental in ... Professional experience with digital advertising platforms like Google Ads or Meta Ads

Junior Software Engineer

OR · On-site +1

$82K - $106K/yr

As a Junior Software Engineer, you'll be paired with a senior engineer who will mentor you as you ... Some experience building software - through professional work, internships, bootcamps, or ...

OR

$180K - $250K/yr

Senior Software Engineer, Infrastructure AcuityMD is a software and data platform that accelerates ... Google Cloud Platform * Terraform * Python, Go, and/or JavaScript (TypeScript) * Building and ...

OR

$114K - $137K/yr

... for a Staff Software Engineer to take it to the next level. In this role, you'll extend the ... Work hands-on with Snowflake (including Snowpark for Python), Google Cloud Platform, Airflow ...

About Automation Engineering Roles at Danaher Are you energized by solving technical problems ... internship start * Experience with hands-on lab testing and technical documentation (e.g., lab ...

About Automation Engineering Roles at Danaher Are you energized by solving technical problems ... internship start * Experience with hands-on lab testing and technical documentation (e.g., lab ...

About Automation Engineering Roles at Danaher Are you energized by solving technical problems ... internship start * Experience with hands-on lab testing and technical documentation (e.g., lab ...

About Automation Engineering Roles at Danaher Are you energized by solving technical problems ... internship start * Experience with hands-on lab testing and technical documentation (e.g., lab ...

OR

$122K - $161K/yr

Contribute to improving software engineering best practices. * Part of an on-call rotation with ... Google Logging and Cloud Trace, troubleshooting regression tests in different environments ...

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Google Software Engineer Internship information

What is the difference between Google Software Engineer Internship vs Google Software Engineer?

AspectGoogle Software Engineer InternshipGoogle Software Engineer
Required CredentialsCurrently enrolled in a Bachelor’s, Master’s, or PhD program; relevant courseworkBachelor’s degree in Computer Science or related field; relevant experience or internships
Work EnvironmentTemporary, project-based, mentored experience during summer or semesterFull-time, ongoing employment with team responsibilities
Employer & Industry UsageInternship program at Google, industry standard for tech internshipsFull-time role at Google, core software development position

The Google Software Engineer Internship is a temporary program designed for students to gain industry experience, while the Google Software Engineer role is a permanent position focused on ongoing software development. Internships often serve as a pathway to full-time employment, with interns gaining valuable skills and networking opportunities. Both roles require strong technical skills, but internships typically have more flexible credentials and are aimed at students seeking industry exposure.

What types of projects do Google Software Engineer Interns typically work on, and how are these projects structured?

Google Software Engineer Interns are usually assigned to real-world projects that are integral to the teams they join. Projects often involve coding, debugging, and collaborating with full-time engineers to develop or improve products and features. Interns are given substantial responsibility, but also receive mentorship and regular feedback from their host and team members. Projects are structured to both challenge interns and help them grow their technical and problem-solving skills, while contributing meaningful results to Google's products or infrastructure.

What are the key skills and qualifications needed to thrive as a Google Software Engineer Intern, and why are they important?

To thrive as a Google Software Engineer Intern, you need strong programming fundamentals, problem-solving abilities, and coursework or experience in computer science, often supported by enrollment in a related degree program. Familiarity with languages like Python, Java, or C++, and exposure to development tools, version control systems, and algorithms is typically expected. Initiative, willingness to learn, effective teamwork, and clear communication are valuable soft skills for excelling in this collaborative and fast-paced environment. These skills and qualities are crucial for contributing to projects, adapting to Google's work culture, and maximizing your learning experience during the internship.

What is a Google Software Engineer Internship?

A Google Software Engineer Internship is a temporary, paid position for students or recent graduates to work on real-world projects alongside experienced engineers at Google. Interns participate in software development, coding, and problem-solving tasks that contribute to Google's products and services. The internship is designed to provide hands-on experience, mentorship, and professional growth opportunities in a fast-paced, innovative environment. Applicants typically need to be pursuing a degree in computer science or a related technical field and demonstrate strong programming skills. The program usually lasts 12-14 weeks and is available in various locations worldwide.
What are the most commonly searched types of Google Software Engineer jobs in Oregon? The most popular types of Google Software Engineer jobs in Oregon are:
What cities in Oregon are hiring for Google Software Engineer Internship jobs? Cities in Oregon with the most Google Software Engineer Internship job openings:
Staff Software Engineer, AI Engineering

Staff Software Engineer, AI Engineering

Tebra

OR

Other

Re-posted 12 days ago


Job description

About the Role

The Revenue Cycle Management (RCM) team is seeking a Staff Software Engineer to lead the design, development, and adoption of AI-native capabilities across our billing and revenue cycle platform.

This role combines deep software engineering expertise with hands-on experience building production AI systems. You will help transform how healthcare organizations manage billing, payments, claims, and operational workflows by applying Large Language Models (LLMs), intelligent automation, retrieval systems, and agentic AI architectures to solve real-world business problems.

As a senior individual contributor, you will operate at the intersection of platform architecture, AI systems engineering, and business transformation. You will influence technical strategy across teams, design reusable AI capabilities, and establish engineering standards for building reliable, secure, and scalable AI-powered systems.

Your impact will come through technical leadership, architectural ownership, hands-on implementation, and your ability to translate complex business challenges into intelligent software solutions that deliver measurable outcomes.

Your Area of Focus
  • Identify and implement practical opportunities to embed AI into backend services and business workflows where it can improve efficiency, accuracy, or decision support.
  • Design and build production-ready AI-enabled services that combine application logic, APIs, and AI models to support real customer and operational use cases.
  • Integrate LLMs, ML models, and external AI services into existing systems using strong engineering patterns for reliability, observability, and maintainability.
  • Build workflows that use AI in a bounded, auditable way, with clear fallback behavior, evaluation, and human review where appropriate.
  • Partner with product, design, data, and operational teams to turn workflow pain points into scalable software solutions with measurable impact.
  • Lead Software Development: Design, develop, test, and deploy scalable and maintainable software applications using Spring Boot, Java, React, and cloud technologies.
  • Architect and Design: Collaborate with product managers, designers, and cross-functional teams to architect robust and scalable solutions that meet business requirements. Provide input into the technical direction of the team and product.
  • Cloud Technology Expertise: Leverage experience with cloud platforms (AWS, Azure, Google Cloud, etc.) to design cloud-native applications. Ensure that applications are optimized for scalability, reliability, and cost-efficiency in a cloud environment.
  • Code Reviews & Mentorship: Conduct thorough code reviews, ensuring that the team adheres to best practices for clean, maintainable, and efficient code. Mentor junior and mid-level engineers, fostering a culture of continuous learning and improvement.
  • Collaboration and Communication: Work closely with product and design teams to define requirements, deliver timely solutions, and provide technical expertise throughout the product lifecycle.
  • Performance and Optimization: Monitor and optimize the performance of applications. Identify bottlenecks and implement performance improvements across both frontend (React) and backend (Java/Spring Boot) layers.
  • Agile Development: Participate in Agile development processes, including sprint planning, daily standups, retrospectives, and backlog grooming. Contribute to defining and prioritizing work within the team.
  • Stay Current: Continuously research and apply emerging technologies and industry best practices to improve the development process and product quality.
Your Professional Qualifications
  • Experience & Seniority: 8+ years of professional software engineering experience building scalable distributed systems, with a track record of driving technical direction and architecture decisions without formal authority.
  • Core Technical Stack: Absolute mastery of Java, Spring Boot, and Python for developing secure, high-throughput, cloud-native backend systems (AWS, Azure, or GCP).
  • Production AI Experience: 2-3+ years of hands-on experience designing, shipping, and maintaining production AI-enabled or AI-native applications (combining LLMs, core application logic, and business workflows).
  • AI Orchestration & Architecture: Practical experience with orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, CrewAI) and a deep understanding of RAG, tool calling, prompt engineering, context/state management, and human-in-the-loop patterns.
  • Systems Infrastructure & Data: Strong background in distributed systems, event-driven architectures, asynchronous processing, and messaging platforms (e.g., Kafka).
  • Production Safeguards & MLOps: Proven experience implementing enterprise AI guardrails, including real-time observability, latency/cost monitoring, automated evaluation pipelines, and robust fallback mechanisms.
  • Collaboration: Impact-driven mindset with excellent cross-functional communication skills to bridge Engineering, Product, Design, and Operations.
  • Advanced Agentic AI: Experience building autonomous, multi-step agentic systems utilizing multi-tier memory networks and recursive reasoning preferred.
  • Domain Expertise: Prior background in Healthcare IT, Revenue Cycle Management (RCM), billing, claims processing, fintech, or similarly regulated, high-compliance transaction environments preferred.
  • Deep Data Retrieval: Hands-on experience with vector databases, semantic search architectures, and enterprise knowledge graph construction preferred.
  • Advanced ML Tooling: Exposure to PyTorch, Hugging Face Transformers, custom embedding models, fine-tuning methodologies, or model serving optimization.
  • Leadership Pedigree: Past experience serving as a Founding Engineer, Principal Architect, or early-stage platform lead driving organization-wide AI/ML adoption frameworks preferred.

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