Senior Backend Engineer – AI Platform

This is us 

Kaltura (NYSE: KLTR) is a global software company on a mission to transform digital experiences from one-way interactions into intelligent, personalized conversations that move people forward.

Founded in 2006, we started by making video more accessible to organizations around the world. Today, we’re taking that foundation much further, combining conversational AI, rich media, enterprise knowledge, and data to build a new generation of intelligent digital experiences.

Our technology helps organizations turn their content and knowledge into interactive, AI-powered experiences that can guide customers, train employees, support learners, and engage audiences in real time. From AI agents and personalized learning experiences to digital events, content hubs, and media platforms, we’re changing how people interact with technology, and what technology can do for them.

More than 1,000 organizations worldwide rely on Kaltura, reaching over 100 million users at home, at work, and at school.

And the people behind it? We’re a global team of 600+ employees, with offices in New York, London, Singapore, and Tel Aviv, united by a culture of openness, flexibility, and collaboration. Kaltura is a fast-paced environment where ideas are welcome, initiative is encouraged, and there’s always something new to build, challenge, or improve. We believe in giving people the freedom to make an impact, the flexibility to balance work and life, and the opportunity to grow as we continue to 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. If this sounds like a place where you’d be excited to learn, contribute, and make an impact, we’d love to hear from you.

The role:

We’re looking for a senior backend engineer to build the core platform behind Kaltura’s agentic AI products. This is backend and distributed systems work at its heart: designing the services, APIs, data stores and async pipelines that power our real-time conversational agents and offline video generation, and making them reliable, observable and multi-tenant at enterprise scale.

You’ll own foundational components (the orchestration engine, a skills and configuration registry, an integration gateway, a memory and retrieval service, evaluation and tracing infrastructure) that multiple product teams and, eventually, customers build on. The AI models already work.

What you’ll do

• Design, build and own backend services and platform components end to end, from architecture and API design through production operation and on-call.
• Build high-throughput, low-latency services that serve both real-time (streaming, strict deadlines) and batch/offline consumers.
• Define service contracts, versioning and extension points so other teams can build on your work without bespoke engineering per customer.
• Drive the platform’s reliability, observability and performance: tracing, metrics, alerting, load testing, capacity planning.
• Lead technical design reviews and make well-reasoned build vs. adopt decisions on open-source and third-party tooling.
• Mentor engineers, raise the bar on code quality and engineering practices, and partner with AI research and customer-facing teams to turn prototypes into production systems.

What you bring

• 6+ years of hands-on backend development building production systems at scale, with Python as a primary language.
• Deep experience with distributed systems: microservices, API design, async processing, message queues/event streaming (Kafka, RabbitMQ, SQS or similar), caching, and concurrency.
• Strong data layer skills with relational and NoSQL databases (e.g. PostgreSQL, Redis, Elasticsearch).
• Production experience in the cloud (AWS or GCP), with containers and Kubernetes, and CI/CD.
• A track record of building shared infrastructure that other teams consume, such as gateways, registries, SDKs or internal platforms. You understand what it takes to ship a platform rather than a feature.
• Strong system design skills and the judgment to balance latency, cost, reliability and delivery speed.
• Familiarity with LLM orchestration frameworks (LangChain, LangGraph or equivalent), agent patterns, or MCP.

Nice to have

• Observability at the platform level with Langfuse or similar, including structured per-request tracing.
• Experience with RAG and vector databases, or with evaluation frameworks for LLM systems.
• Hands-on exposure to integrating LLMs into backend systems (calling model APIs, tool/function calling, retrieval, prompt handling). You don’t need to be an ML expert; we care most that you can build solid systems around these components.

Why this role

You’ll be the engineer who turns proven AI technology into an enterprise-grade platform. Every service you ship is used by multiple teams and many customers, so your work compounds. And if you’re a strong backend engineer who wants to go deep on AI systems, this is a place to do it on real production problems, not demos.

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