לוח משרות דרושים AI Engineer

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage and networking at large-scale. We aim to drive innovations and deliver software defined infrastructure and algorithms to HPC, AI/ML, and Big Data applications.
We are looking for outstanding candidates with hands-on experience in development and optimization of AI frameworks. If you are a team player with excellent communication skills and motivation to revolutionize application performance, youre welcome on board!
What will you be doing?
Work as part of an innovative research team to analyze, develop, test and deploy improvements that enhance Huaweis distributed AI framework.
Develop optimizations that leverage hardware accelerator capabilities, minimize communication overhead and improve training/inference throughput
Push the boundaries of the state of the art in LLM performance and efficiency, including model compression and quantization
Analyze, profile and optimize the latest LLM AI algorithms, and implement as production-quality software libraries for latency-critical use-cases on next-generation hardware.
Work in a distributed computing environment to optimize for both scale-up (multi-device) and scale-out (multi-node) systems
Utilize advanced concepts such as Uncertainty Quantification, Mixed Precision Computing and Model Sparsity to improve performance and enable training of very large AI models
Collaborate with partners from top universities, and open-source communities to conduct state-of-the-art research.

our company, Huaweis Tel Aviv Research and Innovation Center, is looking for an experienced hands-on software architect with expertise in Cloud, AI, and Distributed Systems to join our AI-accelerated Cloud Storage group. The team designs and develops cutting-edge cloud technologies that power next-generation AI applications, optimizing performance, scalability, and efficiency.
The role involves both high-level system understanding and low-level grasp of the connection between storage and AI, to push the boundaries of cloud infrastructure for AI workloads. If you want to be part of something bigger, if you are a team player with excellent communication skills and the motivation to revolutionize AI-driven cloud technologies, youre welcome on board!
What Will You Be Doing?
Research, design, and innovate cloud-based AI acceleration technologies
Analyze AI application performance, identify bottlenecks, and optimize decision-making mechanisms
Collaborate with other engineers to develop AI optimizations, Storage backend and related POCs.
Investigate global trends in AI infrastructure and cloud computing to shape long-term architecture
Collaborate with global teams on next-generation cloud solutions for AI.

You know that feeling when you get an LLM working perfectly in a playground, then realize you need to make it handle real money, real customers, and real uptime? That's where we live.

The GenAI team builds conversational experiences that feel human and decision engines that learn on their own. If moving from prototype to production with millions flowing through it gets you buzzing, keep reading.

What you'll do:

Design, build, and own end-to-end Generative-AI services from first prompt to production rollout.

Combine retrieval-augmented generation (RAG), function calling, and agents to automate underwriting, claims, and customer support flows.

Fine-tune open-source and commercial LLMs on proprietary datasets, evaluate with both offline benchmarks and online A/B tests.

Collaborate with product, data science, and design to invent new AI-first customer experiences (and kill the bad ones fast).

Build scalable APIs and micro-services (TypeScript/NestJS or Python/FastAPI) running in Kubernetes on AWS.

Instrument, monitor, and continuously improve model quality, latency, and cost you ship it, you own it

Mentor fellow engineers on GenAI best practices: prompt engineering, vector search, safety & guard-rails.

Contribute to internal tooling that automates the boring stuff (CI/CD, sandbox environments, branch deploys).

We are seeking a specialist to design and maintain AI-driven workflows and automations using Python, JavaScript, n8n, and no-code tools. The role includes collaborating across teams, building connectors and APIs, and serving as the technical lead for AI initiatives.

Responsibilities:

Design, build, and maintain AI-driven workflows and automations using Python / JavaScript, n8n, and no-code tools.
Collaborate closely with all departments, Marketing, Sales, Customer Success, R&D, Product, and HR teams to identify automation opportunities.
Create connectors and APIs for smooth data and workflow integration.
Work with R&D to align automations with product and engineering stack.
Troubleshoot, optimize, and document automated workflows.
Act as a technical lead for AI initiatives.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.