Senior Software Engineer – Cloud Infrastructure, DevOps

PayPal

Senior engineer building LLM-powered tools and automation for PayPal’s Venmo cloud infrastructure and DevOps teams. Improving reliability, incident response, and developer productivity across AWS systems.

Posted 9/2/2026full-timeSan Jose • Arizona, California, Texas • 🇺🇸 United StatesSenior💰 $123,500 - $212,850 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-powered tools and integrations within cloud infrastructure, with a strong focus on automation, reliability, and scalability. Proven ability to lead engineering teams, mentor junior engineers, and deliver projects on time while adhering to engineering standards.

Highest-signal resume keywords

AI-Powered Tool DevelopmentCloud Infrastructure ManagementPython ProgrammingAWS IaaS and PaaS SolutionsKubernetes and Docker Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software Development LifecycleInfrastructure as Code AutomationLLM and Generative AI FrameworksPrompt EngineeringIncident Triage and Root Cause AnalysisConfiguration ReviewAI/ML IntegrationDevOps PracticesScripting with Bash and GoDistributed Applications Operation

Soft Skills

Strong Communication SkillsMentoring and LeadershipCollaborationProblem-Solving

Tools & Technologies

DockerKubernetesAWS Cloud ServicesLangChainLlamaIndexOpenAI APIAmazon BedrockCI/CD PipelinesObservability PlatformsVector Databases

Industry Keywords

Cloud EngineeringDevOpsSite Reliability Engineering (SRE)AI Best PracticesResponsible AI

Tech Stack

Tools & technologies

AWSCloudDockerGoJavaKubernetesPython

About the role

Key responsibilities & impact

Deliver complete solutions spanning all phases of the Software Development Lifecycle
Act as a project or system leader and coordinate other engineers’ activities
Determine technical tasks for other engineers
Advise management on project-level issues and collaborate on engineering standards
Design and build AI-powered tools and integrations for Venmo’s Cloud Infrastructure and DevOps teams
Develop LLM-powered tools for runbook generation, incident triage, configuration review, and root cause analysis
Develop AI-assisted automation pipelines for provisioning, scaling, deployment, and other infrastructure workflows
Integrate AI capabilities into developer tooling, CI/CD pipelines, and observability platforms
Build and maintain internal AI platforms and APIs for LLM and ML capabilities
Evaluate and drive adoption of emerging AI tools, frameworks, and models
Establish responsible AI best practices, including evaluation, safety, and observability
Mentor junior engineers and lead by example
Define project designs, identify stakeholders, navigate risks and changes, coordinate colleagues’ work, and deliver projects on time and to quality standards
Troubleshoot incidents, identify root causes, document problems, and implement preventive measures
Develop and improve infrastructure and application configuration-as-code automation
Improve infrastructure and operations quality, reliability, and stability
Support the scalability and reliability of Venmo’s AWS cloud infrastructure

Requirements

What you’ll need

5+ years relevant experience and a Bachelor’s degree OR any equivalent combination of education and experience
Bachelor’s in computer science or related field of study
5+ years’ experience in software development or a related field
3+ years’ experience operating distributed applications 24x7x365 as part of a Cloud Engineering, DevOps, and/or SRE team
Extensive hands-on experience designing, implementing, and supporting infrastructure for global-scale services
Deep hands-on experience with IaaS and PaaS solutions from AWS or a similar cloud provider
Hands-on programming and scripting with Python, Java, Bash, and Go
Hands-on experience with Docker and Kubernetes
Hands-on experience building applications with LLMs or generative AI frameworks such as LangChain, LlamaIndex, OpenAI API, or Amazon Bedrock
Experience with prompt engineering, retrieval-augmented generation (RAG), and LLM evaluation techniques
Experience integrating AI/ML capabilities into developer tools, CLIs, chatbots, or internal platforms
Familiarity with AI observability, output safety, and responsible AI practices in production systems
Ability to translate ambiguous engineering pain points into well-scoped AI-powered solutions
Strong communication skills with the ability to explain technical issues to non-technical audiences
Experience with ML model serving, vector databases, or embedding pipelines is a plus

Benefits

Comp & perks

Annual performance bonus
Equity or other incentive compensation, as applicable
Balanced hybrid work model: 3 days in the office and 2 days at the PayPal office or home workspace
Generous paid time off
Healthcare coverage for you and your family
Resources supporting financial security
Mental health support
Reasonable accommodations for qualified individuals with disabilities