Senior Backend Engineer – AI Platform

Kaltura

. Design, build and own backend services and platform components end to end, from architecture and API design through production operation and on-call .

Posted 11/9/2026full-timeIsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in backend development with a focus on building scalable production systems using Python, while ensuring platform reliability and performance through effective system design and observability practices. Proven ability to mentor engineers and collaborate with cross-functional teams to enhance engineering practices and deliver high-quality infrastructure.

Highest-signal resume keywords

Backend DevelopmentDistributed SystemsCloud Production ExperienceSystem Design SkillsLLM Orchestration Frameworks

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Hard Skills

PythonMicroservicesAPI DesignAsync ProcessingMessage QueuesRelational DatabasesNoSQL DatabasesContainersKubernetesCI/CD

Soft Skills

MentoringCollaborationTechnical Leadership

Tools & Technologies

KafkaRabbitMQSQSPostgreSQLRedisElasticsearchLangChainLangGraphLangfuse

Industry Keywords

Platform ReliabilityObservabilityLoad TestingCapacity PlanningShared Infrastructure

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsElasticSearchGoogle Cloud PlatformKafkaKubernetesMicroservicesNoSQLPostgresPythonRabbitMQRedis

About the role

Key responsibilities & impact

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 for real-time streaming and batch/offline consumers
Define service contracts, versioning and extension points for reuse by other teams without bespoke customer engineering
Drive platform reliability, observability and performance through tracing, metrics, alerting, load testing and capacity planning
Lead technical design reviews and make build-versus-adopt decisions on open-source and third-party tooling
Mentor engineers, improve code quality and engineering practices, and partner with AI research and customer-facing teams to turn prototypes into production systems
Own foundational components including the orchestration engine, skills and configuration registry, integration gateway, memory and retrieval service, and evaluation and tracing infrastructure

Requirements

What you’ll need

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
Track record of building shared infrastructure consumed by other teams, such as gateways, registries, SDKs or internal platforms
Strong system design skills and judgment balancing latency, cost, reliability and delivery speed
Familiarity with LLM orchestration frameworks (LangChain, LangGraph or equivalent), agent patterns, or MCP
Nice to have: platform-level observability with Langfuse or similar, including structured per-request tracing
Nice to have: experience with RAG and vector databases, or evaluation frameworks for LLM systems
Nice to have: hands-on exposure integrating LLMs into backend systems, including model APIs, tool/function calling, retrieval and prompt handling

Benefits

Comp & perks

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