Platform AI Engineer
At a glance
Mid-level AI Engineering role at Nexxen. Tel Aviv · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build shared AI capabilities and internal platforms, including knowledge tools, developer aids and common AI services
- Create production agent systems with coordinated agents, tool use, memory and planning
- Connect data intake, retrieval, models and orchestration into complete AI architectures, then deploy and run them
- Assess new models and frameworks, and work with Data Science to turn research into scalable systems
- Set reusable engineering practices, improve system reliability and observability, and guide complex AI projects
What you bring
- A computer science degree or a related qualification, plus at least five years in backend engineering
- At least three years building AI systems for production, with strong Python skills
- Hands-on Kubernetes, Docker and cloud-native deployment experience, plus CI/CD and GitOps delivery skills
- Strong command of LLMs, prompting, reasoning, structured outputs, tool use and retrieval, with end-to-end AI system design experience
Who this fits
This mid-level role suits a hands-on engineer who can build production AI platforms and provide technical guidance to other engineers. You’ll work with Data Science teams and collaborate across engineering; the position is based in Tel Aviv and is hybrid.
From the employer
AI Platform & Innovation Engineer
We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv.
This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across Nexxen’s products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company.
What You’ll Do
Design and build reusable AI platform capabilities used across multiple products.
Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities.
Design and build internal AI platforms such as organizational knowledge (“Brain”), AI developer tools, autonomous engineering workflows, and shared AI services.
Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform.
Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities.
Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment.
Build and operate production AI services using modern cloud-native technologies.
Improve the reliability, scalability and observability of AI systems.
Define engineering standards, reusable patterns and best practices for AI development across engineering teams.
Lead technical proof-of-concepts and drive adoption of innovative AI technologies.
Mentor engineers and provide technical leadership on complex AI initiatives.
What You’ll BringB.Sc. in Computer Science or a related field.
5+ years of backend software engineering experience.
3+ years of hands-on experience building production AI systems.
Strong Python development experience – Must.
Hands-on experience with Kubernetes, Docker and deploying production workloads in cloud-native environments – Must.
Hands-on experience with CI/CD pipelines, GitOps workflows and modern software delivery practices – Must.
Deep understanding of Large Language Models (LLMs), prompting, reasoning techniques, structured outputs, tool calling and retrieval architectures – Must.
Strong experience designing and building end-to-end AI systems, from data ingestion and orchestration to production deployment.
Experience designing AI agents, agentic workflows or AI automation systems.
Experience working with Data Science or Machine Learning teams.
Strong software architecture and distributed systems design skills.
Experience with vector databases, graph databases or modern AI data platforms – an advantage.
Experience with AI frameworks such as LangGraph, OpenAI Agents SDK, CrewAI, Semantic Kernel, AutoGen or similar – an advantage.
Experience evaluating and integrating emerging AI technologies into production systems – an advantage.
Excellent spoken and written English skills.
A proactive, curious and collaborative mindset, with a passion for building AI platforms and driving technical innovation across engineering teams.
What if I have any questions before I apply?
All applications need to be submitted online, however, to discuss any adjustments you may require ahead of submitting your application, please email dkellner@nexxen.com
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