Software Engineer, Enterprise
Twitch
| Company | Twitch |
| Category | Engineering |
| Location | San Francisco |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 29 Apr 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Us
Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.
We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process.
About the Role
Twitch's Enterprise Platform & Technology (EPT) organization is looking for a Software Development Engineer (SDE 2) to architect, build, and operate software systems that power enterprise functions across Twitch and Amazon. This is a hands-on engineering role — you'll write production code, own team-level architecture, and lead multi-engineer projects from design through deployment and operations.
The problems you'll solve don't come with a predefined technology strategy. The business direction is understood — the how is up to you. You'll design and deliver solutions using AWS-native services and AI/agentic patterns, working across domains like Finance, Customer Service, Sales, and Marketing. You'll iterate fast, ship incrementally, and raise the engineering bar for your team through exemplary code, pragmatic design, and mentorship. We need someone who builds, not just advises. You own the architecture and the code.
You Will:
Lead projects requiring work from multiple engineers — owning end-to-end design, integration of parallel work, and delivery across the full software lifecycle (design, implementation, testing, deployment, operations)
Own team-level architecture for enterprise systems, providing system-wide design guidance and ensuring solutions are cohesive, extensible, and secure
Build and operate production applications on AWS-native services (Lambda, Step Functions, DynamoDB, Bedrock, S3, CDK, API Gateway, etc.)
Design and deliver AI-powered and agentic workflows that ship to production — automating business processes, reducing toil, and accelerating delivery
Define agentic architecture patterns and establish best practices for building, testing, and operating AI systems in production — setting the engineering standard for how the team builds with AI
Design and build data pipelines, data lake integrations, and data models that enable clean, reliable data flows across enterprise systems
Drive adoption of engineering best practices on your team; set a culture of robust software development through exemplary code, design reviews, and operational rigor
Actively mentor and coach other engineers, helping them grow their technical skills and independence
Proactively simplify systems, resolve architecture deficiencies, and reduce operational burden — identifying one-way-door decisions and advocating for the right long-term solutions
Communicate technical designs and decisions effectively in writing; develop an understanding of problems that lets you explain them to others in simple, concise terms
You Have:
4+ years of software development experience shipping production systems
2+ years of hands-on experience building AI/ML-powered systems deployed to production
Experimentation with agentic architectures is necessary. And production launch is a
Proficiency in multiple programming languages (e.g., Python, TypeScript/JavaScript, Java)
Experience designing and building applications using AWS-native services — not just deploying vendor software on cloud infrastructure
Demonstrated ability to lead projects involving multiple engineers, owning architecture decisions and integration of parallel work
Experience designing and building data pipelines, data models,
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