דרושים » הנדסה » AI Automation Engineer

Requirements:
4+ years of hands-on software development experience with a focus on AI/ML applications.
Strong proficiency in Python and experience with ML workflows and MLOps.
Familiarity with workflow orchestration tools and/or process automation tools.
Solid understanding of data integration and data-driven solution design.
Ability to work cross-functionally and interface effectively with multiple departments.
Strong initiative and problem-solving skills, with the ability to independently gather requirements and propose solutions.
Passion to AI-driven process optimization, ideally in business domains as mentioned above.
Familiarity with cloud platforms and modern AI frameworks is an advantage

Requirements:
Deep understanding of AI technologies, including large language models
Expertise in prompt engineering and AI-powered automation
Proficiency with AI tools such as ChatGPT, Claude, Midjourney, and Copilot
Knowledge of AI ethics and regulatory considerations
Strong problem-solving and analytical skills
Proficiency with Python or TypeScript for building AI workflows and data pipelines
Excellent communication and leadership abilities
Ability to translate complex AI concepts for non-technical audiences
Experience in project management and cross-functional collaboration
You might also have:
Advanced degree in Computer Science, AI, or related field
Previous experience in AI implementation within an organizational setting
Certifications in relevant AI technologies or platforms
Familiarity with no-code AI application development
Bachelor's degree in Computer Science, AI, or related field.

Requirements:
At least 4-5 years of experience in building production grade backend software systems
Understanding of microservice design and architecture
Strong experience in designing, building and maintaining scalable infrastructures including deployment, DBs, communication
Strong proficiency in Python
Understanding of Machine Learning lifecycle and best practices for AI
Excellent problem-solving abilities, coupled with a creative and strategic mindset
Proven ability to work effectively in a team setting

Requirements:
5+ years of hands-on experience as a Data Engineer, building and operating production-grade data systems.
3+ years of experience with Spark, SQL, Python, and orchestration tools like Airflow (or similar).
Degree in Computer Science, Engineering, or a related quantitative field.
Proven track record in designing and implementing high-scale ETL pipelines and real-time or batch data workflows.
Deep understanding of data lakehouse and warehouse architectures, dimensional modeling, and performance optimization.
Strong analytical thinking, debugging, and problem-solving skills in complex environments.
Familiarity with infrastructure as code, CI/CD pipelines, and building data-oriented microservices or APIs.
Enthusiasm for AI-driven developer tools such as Cursor.AI or GitHub Copilot.

Requirements:
Bachelors degree in Computer Science or a related technical field, or equivalent experience.
4+ years of experience in product management, with a proven track record in SaaS or AI-driven products.
1+ years of hands-on experience building agents based on large language models (LLMs).
Deep knowledge of AI agent frameworks, including but not limited to vibe coding, prompt engineering, and multi-step agent workflows.
Experience with no-code/low-code integration platforms is a plus.
Strong product management skillsdefining product vision, setting strategy, prioritizing features, and driving cross-functional alignment using tools like Jira.
Demonstrated ability to create enablement content, deliver training, and lead product demos for technical solutions.
Excellent interpersonal and communication skills; adept at collaborating with engineers, product managers, sales engineers, and customers.
Passion for innovation, curiosity about emerging AI trends (accessibility is a plus), and a data-driven approach to experimentation.

Requirements:
At least 4-5 years of experience in building ML/AI solutions, specifically in production environment
Strong experience in building and maintaining scalable machine learning infrastructures
Strong proficiency in Python
Solid understanding of Data Science and Machine Learning lifecycle and best practices for model deployment and serving
Excellent problem-solving abilities, coupled with a creative and strategic mindset
Extensive experience with ML frameworks
Understanding of microservice design and architecture
Proven ability to work effectively in a team setting

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:
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.

Requirements:
Experience: At least 3 years of experience in automation infrastructure development.
Programming Skills: Proficiency in Python and Node.js, with a deep understanding of software development principles.
CI/CD Expertise: Proven experience in designing and managing CI/CD pipelines, particularly in cloud environments (e.g., AWS, Azure).
Automation Frameworks: Extensive experience with automation frameworks and libraries, such as Playwright, Pytest, or similar.
Containerization & Orchestration: Hands-on experience with Kubernetes and Docker.
Version Control: Strong knowledge of version control systems, particularly Git, and best practices for collaboration and code management.
Problem-Solving: Excellent analytical and problem-solving skills, with the ability to troubleshoot complex infrastructure issues.
Web Technologies: Familiarity with web technologies, including HTTP, JSON, HTML, and JavaScript.
Languages: Excellent communication skills in both Hebrew and English.
Adaptability: Ability to work effectively in a fast-paced, multi-tasking environment.

Requirements:
5+ years of experience in AI/ML engineering or applied machine learning roles.
Proven experience designing, developing, and scaling production-grade AI systems (LLMs, conversational AI, or agent-based systems preferred), preferably based on known agents frameworks such as LangChain, LangGraph
Advanced proficiency in Python and experience writing clean, maintainable, and testable code.
Strong background in prompt engineering, LLM orchestration, and model evaluation.
Demonstrated ability to drive technical initiatives across disciplines (engineering, product, and data science).
Excellent communication skills with the ability to translate complex ideas into practical solutions.
Ability to work in cross-functional teams and communicate technical decisions clearly.