AI Tech Lead

The role

Kaltura is looking for an AI Tech Lead to join our M&T engineering organization - the team behind a live, high-availability TV platform serving telecom and media companies worldwide at 99.995% SLA on AWS.

We're not looking for someone who talks about AI strategy. We're looking for someone who picks up a real problem, finds where AI creates a step-change, and makes it happen.

This is an individual contributor role reporting directly to the VP R&D. You'll be embedded in M&T but will work closely with engineering teams across Kaltura R&D — contributing your AI expertise to shared initiatives, building collaborative relationships, and helping move technical work forward together.

If you're the kind of engineer who gets restless when there's a better way and no one is building it yet — this role is for you.

The day-to-day

• Lead AI-driven initiatives across M&T engineering — from scoping and architecture through hands-on execution
• Drive adoption of AI tooling and practices across Dev and DevOps teams, both within M&T and cross-org
• Identify opportunities where AI can improve engineering velocity, incident response, cost efficiency, and system reliability. Work across teams and departments — align stakeholders, unblock dependencies, and keep initiatives moving
• Collaborate with group managers and engineers to translate AI capabilities into practical, production-grade solutions
• Stay ahead of the curve: evaluate emerging AI tools, frameworks, and approaches and bring the relevant ones in

Ideally, we’re looking for:

• 7+ years of software engineering experience, with at least 3 years focused on AI/ML in production environments
• Hands-on experience with both Dev (backend services, APIs, microservices) and DevOps (CI/CD, infrastructure, observability, cloud operations)
• Proven experience building or integrating AI/ML solutions in cloud-native, distributed systems (AWS preferred)
• Strong understanding of observability concepts: metrics, logs, traces, alerting, anomaly detection T
• Experience driving technical initiatives across multiple teams without direct authority
• Excellent communication skills — ability to translate complex AI concepts for non-AI engineers and push for outcomes in a multi-stakeholder environment

These would also be nice:

• Experience with LLMs, RAG pipelines, or AI agents applied to engineering operations (AIOps)
• Familiarity with Kubernetes, Grafana, or similar operational tooling
• Background in media tech, video streaming, or telecom platforms
• Experience with Databricks, MLflow, or similar ML platform tooling
• Track record of introducing AI tooling that improved team velocity or system reliability at scale

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