דרושים » AI » Senior AI Engineer

Requirements:
Msc. in Computer Sciences / Software Engineering from a leading university.
4+ years of experience of software development, with a focus on algorithms design and validation.
Experience designing and building AI-driven systems utilizing LLMs, and other solutions.
Familiarity with LLM-based patterns such as RAG, Agentic-workflows, production level prompt-engineering.
A passion for exploring new ideas using the latest ML, DL, and Gen-AI solutions.
Great communication, interpersonal and problem solving skills.

Requirements:
What Experience Will Drive to Success
* Bachelors degree in data Science, Computer Science, Computer Engineering, or related field.
* 3+ years of hands-on software development experience.
* 1+ years of experience in AI engineering, with a proven track record of building and deploying AI systems.
* Strong proficiency in Python.
* Experience with AI frameworks and protocols such as LangChain, LangGraph, OpenAI, MCP, A2A, etc..
*  Solid understanding of LLM integration and prompt engineering for complex reasoning.
* Experience with Git and Jenkins.
* Strong problem-solving skills, a passion for innovation, and a self-driven mindset.
* Excellent communication and collaboration skills.
*  Hands-on experience with Big Data processing frameworks (Advantage).
*  data science experience or familiarity with applied Machine Learning (Advantage). What We Are Looking For Independent and Self-Driven: Were building an AI Department from the ground up, so we need someone proactive, takes ownership, and thrives in a startup-like environment. Passion for Innovation: Whether its building scalable data infrastructure or creating advanced AI models, we are looking for someone passionate about solving complex challenges and delivering innovative solutions. Collaboration Skills: we are all about teamwork. You will collaborate with engineers, data scientists, and product teams to build impactful solutions. Strong communication and interpersonal skills are key. Adaptability and Problem-Solving: Things move quickly at our company. You should be able to adapt to changing requirements and quickly solve problems in a fast-paced, dynamic environment. Can-Do Attitude: Were seeking motivated individuals who take the initiative, face challenges head-on, and can work independently while contributing to the team's success. About the Company: our mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With us, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines. Leading financial, healthcare, m-commerce, consumer, and B2B brands use our company to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and businesses globally. Today, our customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.

Requirements:
A degree in Computer Science, Engineering, or a related field
5+ years of experience
Knowledge of HPC and AI solution technologies from CPUs and GPUs to high speed interconnects and supporting software
Experience with job scheduling workloads and orchestration tools such as Slurm, K8s
Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc.
Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies.
Python programming and bash scripting experience.
Comfortable with automation and configuration management tools such as Jenkins, Ansible, Puppet/chef
Deep knowledge of Networking Protocols like InfiniBand, Ethernet
Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix)
Ways to stand out from the crowd:
Familiarity with cloud computing platforms (e.g. AWS, Azure, Google Cloud)
Knowledge of CPU and/or GPU architecture
Knowledge of Kubernetes, container related microservice technologies
Experience with GPU-focused hardware/software (DGX, Cuda)
Background with RDMA (InfiniBand or RoCE) fabrics.

Requirements:
5+ years of professional software development experience, with JavaScript and web technologies. (Java advantage)
2+ years of experience of server-side development with Node.js.
2+ years of experience of Client-side development with React.
Experience in designing and developing large distributed systems and microservices architecture.
Experience working with NoSQL and Relational DBs.
Experience working with large scale applications - advantage.
Experience working with Cloud providers such as AWS Must.

Requirements:
About You:
Proven experience in a relevant technical role such as QA Automation / Software Engineering / Product / Engineering Support required. Experience with TEST planning and documentation background in QA. Automation frameworks - advantageExperience in both manual and automated testing - advantage.
Strong problem-solving capabilities with an analytical mindset.
Self-driven learner with the ability to master new technologies quickly.
Exceptional English communication skills, both written and verbal.
Proven ability to thrive in a fast-paced, dynamic environment.
Strong multitasking abilities with excellent attention to detail.
Collaborative mindset with the ability to work effectively across teams.
Passionate about exploring and implementing emerging technologies.

Requirements:
B.Sc. in Computer Science or a related field.
5+ years of experience in backend software development, including system design and architecture.
Proficiency in at least one backend programming language (We write in Go).
Strong understanding of microservices architecture, RESTful APIs, and relational databases.
Deep familiarity with Kubernetes and the cloud-native ecosystem.
Demonstrated ability to tackle complex technical challenges and deliver high-quality solutions.
Ways to stand out from the crowd:
Expertise in Kubernetes internals and advanced cloud-native technologies.
Hands-on experience with HPC or AI/ML platforms.
Familiarity with AI inference workloads and performance optimization.
Proficiency in Linux, with knowledge in networking, security, storage, and virtualization.

Requirements:
2+ years of experience as an AI engineer or applied ML engineer working with LLMs (e.g. OpenAI, Claude, Mistral, etc.).
Proven experience with LangChain and/or LangGraph to build real-world AI agents or workflows.
Proficiency in Python/Type script, with hands-on experience in LLM frameworks and orchestration tools.
Experience designing and deploying autonomous agents, memory modules, and tool-using systems.
Familiarity with vector databases (FAISS, Pinecone, Weaviate, etc.) and knowledge retrieval systems.
Solid understanding of NLP workflows, prompt engineering, and tokenization strategies.
Experience with RESTful APIs and backend data integration.
Strong debugging, problem-solving, and architectural design skills.
Experience with Typescript, especially in AI agent or tool integration.
Prior experience deploying AI in production systems.
Familiarity with MLOps and CI/CD pipelines for AI-based applications.
Experience working with cloud platforms (AWS / GCP, or Azure).
MSc in Machine Learning, Computer Science, or a related technical field.

Requirements:
BSc in Computer Science/Software Engineering or equivalent knowledge.
At least 2 years of experience in backend development.
Experience working with Python for building applications or services.
Experience working in a cloud environment (AWS - Advantage).
Knowledge of modern database technologies.
In-depth knowledge of object-oriented programming principles and design patterns.
Excellent verbal and written communication skills.
Experience with high-performance, multi-threaded, multi-processed environments - Advantage.
Experience developing a high-scale, multi-tenant cloud SaaS mission-critical applications - Advantage.

Requirements:
6+ years of experience in infrastructure and Backend SW development roles.

Experience managing infrastructure on AWS.

Experience with architecture methodologies and paradigms like micro-services, distributed systems and more.

Experience integrating and actively using GenAI tools (e.g., GitHub Copilot, Claude, ChatGPT etc) in daily development must.

Open-minded to new workflows and AI-driven innovation.

An agile/DevOps way of thinking.

Experience with CI/CD tools (Jenkins, argot, Nexus and similar).

Experience with the K8S platform and tools (Helm charts and similar).

Experience with the following technologies/tools/fields: Elasticsearch , Clickhouse, Messaging (Kafka,NATS,, Redis etc), Monitoring and Visibility (Prometheus, Grafana, loki, etc).

Programming languages Golang/ Java.

Functioning well under pressure.

Strong problem-solving ability and a "Can-do approach".

Working in an agile environment.

Excellent communication and interpersonal skills.

Requirements:
3+ years of experience in MLOps, ML infrastructure, or AI platform engineering.
2+ years of hands-on experience in ML pipeline automation, large-scale model deployment, and infrastructure scaling.
Expertise in deep learning frameworks (like PyTorch, TensorFlow, JAX) and MLOps platforms (like Kubeflow, MLflow, TFX).
Proven track record of building production-grade ML systems that scale to billions of predictions daily.
Deep knowledge of Kubernetes, cloud-native architectures (AWS/GCP), and infrastructure as code (Terraform, Helm, ArgoCD).
Strong software engineering skills in Python, Bash, and Go, with a focus on writing clean, maintainable, and scalable code.
Experience with observability & monitoring stacks (Prometheus, Grafana, Datadog, OpenTelemetry).
Strong background in security, compliance, and model governance for AI/ML systems.
Leadership & Execution:
Proven ability to lead high-impact engineering teams in a fast-paced AI environment.
Ability to drive technical strategy while remaining hands-on in critical areas.
Strong cross-functional collaboration skills, working closely with research and engineering teams.
Passion for automation, efficiency, and designing scalable self-service MLOps solutions.
Experience in mentoring and coaching engineers, fostering a culture of innovation and continuous learning.
It Would Be Great If You Have:
Experience working with LLMs and large-scale generative AI models in production.
Expertise in optimizing model inference latency and cost at scale.
Contributions to open-source MLOps tools or AI infrastructure projects.