What You'll Be Doing:
- Design and build internal platforms and developer tooling to supercharge engineering productivity.
- Implement AI-powered solutions to improve code quality, CI/CD pipelines, observability and testing workflows.
- Champion Developer Experience (DX) — streamline onboarding, local development, release processes and overall dev velocity.
- Co-own the architecture of platform services used across CloudWalk’s engineering organization.
- Collaborate closely with Product, SRE, and QE teams to drive platform-first thinking and foster a culture of quality and productivity.
- Continuously experiment with LLMs, AI-powered development tools, and emerging technologies to innovate in internal tooling and platforms.
Required Skills:
- Solid software development foundation (Ruby, Go, JavaScript, Rust, or Dart).Practical experience with LLMs (GPT-4, Claude) and AI-assisted development workflows.
- Expertise in prompt engineering and AI model interaction (applied to software engineering use cases).
- Deep understanding of modern software development, cloud-native architectures, and dev workflows.
- Strong engineering practices: automation, testability, resilience, maintainability.
- Excellent cross-team communication and collaboration.
Nice to have:
- Proven ability to design and implement developer-facing tools, CI/CD pipelines, observability stacks.
- Experience with CI tools and cloud environments (GCP, AWS).
- Background in ML/AI testing frameworks.
- Experience with cloud-native AI services.
- Knowledge of Relational Databases, SQL, and ORM technologies.
This Role Isn’t For You If:
- You lack hands-on experience with AI-assisted development
- You don’t believe AI can handle the majority of the work.
- You're not excited about continuous learning in emerging technologies.
The Future We See:
- At CloudWalk, we envision a future where engineering velocity and developer joy are first-class concerns:
- Empowering every engineer with AI-enhanced development environments and intelligent tooling.
- Reducing friction and cognitive load in engineering workflows.
- Creating platforms that scale with the organization, unlocking quality and speed at every level.
- Bringing AI innovations to enhance not only products, but also the way we build them.
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