DevOps Engineer

Description

This is us 

Kaltura’s (NYSE:KLTR) mission is to power any video experience for any organization – live, on-demand, or real-time. We not only want to make using video simpler, but we also want to better people’s lives through video. Founded in 2006, Kaltura is now a global leader in the video market with millions of people using our products daily to teach, learn, watch, connect, and collaborate. Among our customers, you’ll find more than 1000 global, well-known organizations.    

15+ years since starting the company, we continue to foster a diverse and collaborative work environment where everyone gets a say. Our team is currently 700+ people, and we’re still growing. We have offices in New York, London, Singapore, and Tel Aviv, but our technology is all in the cloud. 

Kaltura has a fast-paced environment where initiative is always encouraged. Together with our hybrid work model and flexible state of mind, you get the right conditions for creative juices to flow freely. Thanks to our long line of products, cultivation of rich collaborative culture and care for each Kalturian, you’ll never run out of room to grow and evolve.   

If you don't meet 100% of the requirements below - that's okay, nobody's perfect! We believe in hiring people, not just a list of skills. We encourage you to apply if you think this is a role that would make you excited about coming to work every day. 

Requirements

The role 

You will join a global DevOps & Platform team responsible for designing and operating distributed production systems at very high scale, with a relentless focus on quality, robustness, and reliability. We provide Kaltura with the tools it needs to push forward product innovation and scale in the age of AI. 

You will own projects end-to-end, drive new implementations forward, and act as a technical partner across the organization. You'll work closely with the Platform teams, Development teams, Architects, AI/ML Researchers, and Product, translating complex needs into resilient systems that scale. 

We're looking for someone who takes ownership, who can see a problem or a need, shape the solution, and carry it all the way to production. 

The day-to-day 

• Lead initiatives end-to-end, from design through implementation to production rollout, owning the outcome, not just the task
• Design, build, and operate highly available, distributed systems at scale on AWS and GCP, with a strong emphasis on quality and robustness
• Work across the full platform stack, Kubernetes, Docker, and Helm, CI/CD and automation, and the data, caching, and messaging layers (Mongo, MySQL, Postgres, Redis, Kafka, and more)
• Modernize and consolidate different stacks and architectures into Kaltura's single, coherent platform
• Build and operate the infrastructure behind our AI workloads, including GPU inference and the platforms that serve them
• Drive system reliability, monitoring, and observability, and troubleshoot complex issues across application, infrastructure, networking, OS, and data layers
• Collaborate across Platform, Development, Architects, AI/ML Researchers, and Product, and leverage modern AI coding tools to work at high velocity and quality

Ideally, we’re looking for:

• 2+ years of hands-on experience in DevOps / Platform / SRE roles, operating distributed production systems at high scale, with a proven ability to lead projects independently and drive new implementations end-to-end
• Deep hands-on expertise with AWS in production (EKS, ECS, S3, EC2, CloudFront, IAM, Bedrock, MSK, Lambda, Cloudwatch) including Infrastructure as Code (Terraform or similar)
• Deep hands-on expertise with Kubernetes and Helm, including a strong understanding of how Kubernetes internals work and how to operate them in production, alongside Docker / containerized systems
• Strong knowledge of networking and operating systems (TCP/IP, DNS, load balancing, Linux internals)
• Strong experience with CI/CD and automation (GitHub Actions), monitoring and observability (metrics, tracing, logging, tools like Prometheus / Grafana)
• High proficiency with current AI coding tools, including a deep understanding of how they work and how to apply them to drive real productivity.

These would also be nice:

• Experience integrating or migrating systems between different stacks or organizations
• Experience driving cross-team technical initiatives
• Experience working with GPUs for inference and serving AI/ML workloads

The perks:

1. Hybrid, flexible work environment  
2. Extended private health (including mental) insurance  
3. Personal and professional development programs 
4. Occasional Cross company long weekends