Staff Software Engineer, AI/ML
Crunchyroll, LLC
| Company | Crunchyroll, LLC |
| Category | Engineering |
| Location | Hyderabad |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 9 Jun 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer career page (greenhouse) |
Description
About Crunchyroll
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.
Join our team, and help us shape the future of anime! About the role:
Enterprise Technology is building the core AI-native engineering capabilities needed to improve how we design, build, test, and ship software. This role will help apply AI-assisted engineering across Enterprise Technology projects while maintaining strong quality, security, and production-readiness standards.
You will build production software, direct AI coding agents, review AI-generated work, improve delivery practices, and help turn what works into reusable patterns for future Enterprise Technology initiatives.
What You’ll Do:
Build and ship production software for Enterprise Technology initiatives, including services, APIs, data models, user interfaces, integrations, tests, and operational tooling.
Direct AI coding agents by writing clear specs, acceptance criteria, implementation plans, and verification steps.
Review and own AI-generated code, tests, pull requests, and migrations for correctness, security, maintainability, and production readiness.
Help establish repeatable AI-assisted engineering practices for Enterprise Technology projects.
Design and implement integration-heavy, data-intensive, and workflow-driven systems for enterprise applications and operational platforms.
Apply and extend AI-assisted engineering tooling, including coding-agent workflows, repo access patterns, context setup, automated verification, and reusable delivery templates.
Track practical delivery metrics such as cycle time, quality, rework, test coverage, cost, adoption, and operational health.
Partner with Product, Security, business stakeholders, and Enterprise Technology teams to deliver secure, maintainable software.
Improve testing, review, observability, documentation, and operational practices for AI-assisted delivery.
What We’re Looking For:
12+ years of experience building and shipping production software as a hands-on engineer, senior IC, technical lead, or Staff-level contributor.
Strong production experience with Python and/or TypeScript across backend, frontend, data, API, or cloud-native systems.
Hands-on experience using AI coding agents or tools such as Claude Code, Google Antigravity, Codex, Cursor, or similar systems.
Strong engineering judgment for reviewing AI-generated code and knowing where human oversight is required.
Experience building or integrating services, APIs, relational data stores, event-driven systems, and user-facing workflows.
Familiarity with cloud-native development, preferably GCP, including CI/CD, monitoring, security scanning, and cost-aware engineering.
Understanding of secure engineering practices, role-based access, SSO, audit logging, and controls for enterprise systems.
Ability to influence technical decisions, mentor engineers, and raise quality across a significant system or project area.
Clear written and verbal communication with engineering and non-engineering stakeholders.
Preferred qualifications:
Experience with enterprise systems, business applications, workflow platforms, data platforms, or internal tools.
Experience with media, streaming, content platforms, or complex business domains.
Experience building developer-facing tools, templates, or internal platforms that help engineers ship software faster and more safely.
Experience with LLM or agent observability tools such as Datadog, LangSmith, Langfuse, or similar systems.
Experience with data migration, compliance-sensitive systems, SOX controls, aud
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