About the Role
At Geniez AI, we're building the enterprise Generative AI framework that fundamentally changes how large organizations manage their most critical business platforms and how they build AI-powered applications to derive insights from core business data.
As an early engineering hire, you'll architect and build the hybrid cloud infrastructure that powers our framework across the largest enterprise environments, with unique performance requirements, security constraints, and scale needs.
This isn't about maintaining existing infrastructure. You'll be making foundational decisions about how our framework deploys, scales, and operates in enterprise environments. Your work will directly enable our largest customers to adopt and scale our solution with confidence.
This role is open to candidates from the US, UK and Israel.
What You'll Build
- Data infrastructure for AI: Build robust data pipelines using Python, Spark and other tools that power our agentic workflows and AI agents at enterprise scale
- Hybrid cloud architecture: Design and implement our Kubernetes-native deployment model that works seamlessly across on-prem, AWS, Azure, GCP, and hybrid environments
- Deployment automation: Create tooling that makes deploying and upgrading our framework easy and reliable for customers with varying technical sophistication
- Observability systems: Build monitoring, logging, and diagnostics that help both our team and customers understand system health, usage and performance
- Internal CI/CD & testing: Evolve our internal development pipeline with automated testing frameworks, integration tests, deployment pipelines, and quality gates that let us ship confidently and frequently
What We're Looking For
Required:
- Python, Java, Typescript expertise: You write modern, clean, maintainable code and have shipped production systems with it
- Kubernetes in production: Hands-on experience deploying and operating workloads on Kubernetes
- Distributed computing: Real experience with Spark or similar data processing frameworks at large-scale
- DevOps mindset: You think in terms of automation, reproducibility, and infrastructure-as-code
- Systems thinking: You understand how pieces fit together, including networking, storage, security, observability and scale
- Ownership mentality: You'll wear many hats and own outcomes, not just tasks
Bonus Points:
- Experience deploying agentic AI workflows in production at scale
- Worked with enterprise customers on deployment/integration
- Experience with Helm, Terraform, or similar tools
- Experience building enterprise software in Java and Typescript
- Understanding of enterprise security/compliance requirements (SOC2, etc.)
- Understanding of Mainframe computers and operating systems
Why Join Us
Early-stage impact: Your decisions will shape how our product works for years. You'll have direct influence on architecture, technology choices, and team culture.
Enterprise scale from day one: Our customers are all major enterprises and Fortune 500 companies. You'll solve problems that matter at massive scale, with the urgency and autonomy of a startup.
Backed by top investors: We're well-funded by leading VCs with runway to build something significant with focused execution.
Small, technical team: We’re a tight group of talented people solving hard problems together.
Learn constantly: You'll work alongside experienced engineers, get exposure to cutting-edge AI applications, and tackle problems you haven't seen before.