לוח משרות דרושים AI Engineer

We are looking for an experienced ML/AI engineer to anchor our ML Platform team. You will lead the effort to productize our Large Language Models, transforming experimental code into robust, efficient services. Your goal is to build the infrastructure that allows our Data Scientists to move fast without breaking production.

What you'll be doing:
Model Development & Optimization

Fine-tuning & Engineering: Develop and fine-tune LLMs/classic models for specific medical tasks (condition detection, dialogue systems) using internal datasets.
Research to Production: Partner with Data Scientists to develop experimental code into scalable, production-ready modules.
Platform Engineering & Infrastructure

Pipeline Orchestration: Build and maintain complex ML workflows using Kubeflow Pipelines (KFP) or similar orchestration tools.
Internal Tooling: Develop and manage the internal Python ecosystem-libraries, SDKs, and utilities-that the Data Science team uses for daily development.
CI/CD & Automation: Write and maintain CI/CD scripts to automate the testing, versioning, and deployment of machine learning artifacts.
Production Standards & Integration

System Integration: Work with backend developers to integrate trained models/agents into the core application architecture.
Code Quality: Enforce high engineering standards through code reviews, ensuring that research code meets production reliability and maintainability requirements.
Requirements Engineering: Translate evolving data science requirements into concrete infrastructure and platform features.

We are looking for a hands-on AI Engineer to help build our core intelligence engine and infrastructure. In this role, you will work on exploring and building autonomous solutions that execute security workflows end-to-end, moving capabilities from research concepts to scalable production features.
What You Will Build
● Internal AI Infrastructure: Contribute to a shared internal AI platform for models, data, training, and observability.
● Autonomous Capabilities: Build solutions that automate complex security operations and investigative workflows.
● Active Defense Mechanisms: Help productize runtime guardrails into customer-facing protective controls and monitoring systems.
Responsibilities
● Develop and implement the engineering backend for AI-driven security features.
● Build and maintain the internal mechanisms that allow for safe and scalable AI feature deployment.
● Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
● Implement runtime guardrails and AI-focused data security capabilities.

We are looking for a visionary AI Lead to build our internal AI platform and architect adaptive intelligence systems that serve as a dedicated security architect for each of our customers. You will lead a team of AI Researchers and Engineers to move beyond simple integrations and build true autonomous security solutions.
What You Will Build
● Autonomous Workflows: Build agents that execute security workflows end-to-end, automating detection, investigation, and response processes.
● Runtime Defense: Productize research into active runtime guardrails and defensive control mechanisms.
● Internal AI Platform: Build the shared infrastructure for models, training, and evaluations to enable safe, scalable AI features across the organization.
● Adaptive Intelligence: Oversee the development of models that learn from customer-specific environments to generate high-signal, personalized insights.
Responsibilities
● Lead the AI Research Group, managing AI Researchers, Engineers, and DevOps.
● Own the intelligence engine end-to-end, delivering next-generation analytics and contextual visualization features.
● Drive the strategic "build vs. partner vs. buy" decisions for cloud prevention and AI controls.
● Collaborate with the Threat Team to develop AI-driven threat detections against emerging attack vectors and novel AI threats.

Were seeking a Team Lead - Generative AI Engineer to lead a team of engineers in designing, developing, and deploying production-grade AI systems. This role is ideal for someone who is both a strong technical contributor and an experienced people leader-capable of driving architecture decisions, mentoring team members, and delivering innovative AI solutions at scale.
You will be responsible for guiding the end-to-end lifecycle of Generative AI applications, ensuring technical excellence, scalability, and alignment with business needs. This includes working across backend systems, RAG pipelines, prompt engineering, and cloud-native deployments.
Key Responsibilities
Leadership & Team Management Lead and mentor a team of AI/ML engineers, fostering growth and technical excellence.
Define and enforce coding standards, architectural patterns, and best practices.
Collaborate with stakeholders to translate business needs into AI-driven solutions.
Manage project timelines, technical risks, and team deliverables.
Generative AI & Prompt Engineering Integrate and optimize applications using LLM provider APIs (OpenAI, Anthropic, etc.).
Design prompts with advanced techniques (few-shot, chain-of-thought, chaining, context crafting).
Implement safeguards (guardrails, structured output validation, injection protection).
Architecture & Backend Development Build scalable backend services in .NET (C#) and Python, working with SQL and APIs.
Develop and manage RAG pipelines, conversational AI systems, and summarization tools.
Drive observability: tracing, logging, monitoring for LLM-powered systems.
Evaluation & Optimization Benchmark and evaluate LLMs using custom datasets and automated testing.
Oversee system reliability, performance tuning, caching, and optimization.
Ensure solutions meet enterprise-grade standards for security and scalability.

We are looking for a highly skilled AI Engineer to join an advanced R&D environment within the security sector.
Responsibilities:
Develop advanced Python-based systems and integrate a variety of AI models into software solutions.
Implement and deploy AI models in On-Premise environments, including full integration within existing systems.
Work closely with a multidisciplinary team in a dynamic, innovative technological environment.

We are seeking an experienced ASIC AI/ML Engineer with deep expertise in AI/ML infrastructure and application development specifically for semiconductor design verification disciplines. The ideal candidate will have a proven track record of delivering end-to-end AI solutions from concept to large-scale production deployment.
In this role, you will collaborate directly with architects, designers, verification engineers, software teams, and backend specialists to define best practices and deploy production-ready AI-driven workflows and applications. Your focus will be on implementing LLM, GenAI, and classical ML solutions that transform our ASIC design verification processes and accelerate our path to tape-out.
Key job responsibilities
Develop and maintain scalable AI/ML infrastructure for ASIC design and verification teams
Architect, develop, and deploy production-ready AI/ML applications for semiconductor design workflows
Design and implement GenAI solutions including LLMs and agentic AI systems for verification processes Invent innovative AI-driven solutions to eliminate identified inefficiencies in design and verification flows
Establish best practices and standards for AI/ML application development in semiconductor environments
Create monitoring and observability frameworks for AI model performance in production design environments
Collaborate cross-functionally with architects, designers, verification engineers, and software teams
Research and evaluate emerging AI technologies for applicability to semiconductor design challenges.

we are seeking for an AI Engineer! Key Responsibilities: Prompt Engineering & Optimization: Design, write, and optimize complex prompts ( system Prompts, Chain-of-Thought) to maximize performance across various LLMs. AI Agents Development: Build intelligent agents capable of executing multi-step actions, decision-making, and interaction with external systems. RAG Systems: Design, implement, and maintain Retrieval Augmented Generation (RAG) architectures connecting models to organizational knowledge. Python Development: Develop high-quality Python code, work with LangChain / LlamaIndex, and integrate AI solutions into company products. Research & Evaluation: Explore new AI tools, evaluate model performance, and continuously improve AI outputs.

abra is seeking for an experienced AI Engineer We are looking for an engineer to join the infrastructure team and lead the development of systems around Large Language Models (LLM) – in an advanced, stable, and pleasant technological environment. The role includes:
* Building smart, measurable, and secure production infrastructures.
* Developing and deploying end-to-end LLM services, including construction and optimization.
* Working with MCP and exposing tools.
* Collaborating closely with Product, Data, and DevOps teams, including writing clean code and performing CI/CD tests. Full-time position, Sunday to Thursday, located in Haifa.

Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

Join an amazing team driving cutting-edge AI solutions in the fintech industry, primarily focused on evaluating risk for lending products.
This Principal role requires an exceptional blend of deep research, architectural mastery, and a powerful innovation mindset to pioneer new capabilities and deliver high-quality, end-to-end AI systems that shape the product direction for the next 5-10 years.
Responsibilities:
System Architecture & Ownership
Own projects from conception to production, collaborating globally with partners to deliver complex projects.
Define the vision and direction for end-to-end solutions, serving as a thought leader on execution that brings immediate value and solves for the long-term vision.
Deliver robust, high-performance AI/ML system designs that meet critical requirements (latency, throughput, cost, maintenance).
Drive cross-functional end-to-end design architecture.
AI/ML Development & Leadership:
Lead the full cycle of big data exploration, including hypothesis formulation, advanced predictive statistical modeling, and algorithm development across complex, large-scale data.
Mentor existing Data Science teams, influence AI-driven product design and strategy with partner architects, and assist in the definition of roles and training needs.
Innovation & Research Strategy
Pioneer innovative Proof of Concepts (POCs) to show the way for where Fintech products should go over the next 5-10 years, focusing on high-impact solutions like Explainable AI, Homomorphic Encryption, or advanced Behavioral Analytics.
Apply research to create high-impact solutions and represent the teams innovation to the wider organization.
Act as a Consultative Business Facilitator, exploiting revealed insights and providing entrepreneurial guidance for business stakeholders.

Come join the team as a Senior Staff AI Engineer.
Our Data Exchange group is responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all products.
You will utilize your skills to help develop and maintain backend services leveraging AI and machine learning models, using both analytical algorithms and deep learning approaches, to acquire data from financial institutions on behalf of our users.
Responsibilities:
Lead and apply best practices in AI driven software lifecycle management, from ideation, through development and evaluation to production deployment.
Build a backend service with AI in its core at scale (millions of users and requests daily)
Collaborate with stakeholders to define success criteria and align model metrics with business goals
Work side-by-side with product managers, business analytics, data scientists, and backend engineers in enabling AI solutions for business use cases
Explore the state-of-the-art technologies and apply them to deliver customer benefits

You will be part of REM (Road Experience Management) department, which is responsible for the automatic High-Definition map-making process, which is a key technology in autonomous driving and high-end Driving Assistance systems.

Vision-based localization is a key enabler for utilizing and creating the maps. Our group is responsible for aligning the map with the world, and reporting detected changes during the drive. Our technology is safety-critical, and the code has strict time and memory constraints as it operates in real time.
What will your job look like:
Develop and optimize computer vision and deep learning algorithms to accelerate data generation and labeling workflows for autonomous driving
Apply both classical computer vision techniques and modern deep learning methods to solve large-scale data challenges
Collaborate closely with development and annotation teams to enhance automation and ensure high-quality data
Own the entire lifecycle from prototyping to scalable deployment within internal pipelines and tools
Develop tools to evaluate and analyze algorithm performance, robustness, and operational efficiency

We are looking for a talented and experienced AI Backend Engineer to join our dynamic Engineering team. This is a hybrid role, reporting to the Group Manager, Director, Software Engineering in the Engineering Department. Avalor curates and contextualizes data from hundreds of security and business tools to help companies understand and address their riskiest problems. If you're passionate about data and helping companies improve their security posture, youll play a critical role in driving innovation within the AI space by leveraging cutting-edge backend technologies.
What youll do (Role Expectations):
Lead and drive innovative projects within the AI domain, leveraging fabric capabilities to enhance and accelerate our products offerings
Develop our agentic fabric framework and implement the agentic fabric framework across the platform
Identify opportunities to address complex technical challenges and improve existing systems
Own the end-to-end delivery of projects, from proof-of-concept (POC) to full-scale production deployment
Stay updated on industry trends, emerging technologies, and best practices to continually enhance our technology stack and processes.

Shape the Future of Cybersecurity with Us Are you driven by deep curiosity, bold innovation, and the desire to transform cutting-edge AI research into real-world cybersecurity impact? Join Cynet, an established yet rapidly growing cybersecurity startup, where you’ll help build next-generation AI-powered security products from the ground up. You’ll be part of a small, elite, cross-disciplinary team working closely with security researchers, R&D engineers, data engineers, and product leaders.
Here, you’re not just joining a company, you’re stepping into a place where you can envision, build, and deploy foundational AI technologies that protect organizations worldwide. You will have the rare opportunity to drive innovation end-to-end, shape our future technology, and create AI systems that make a real difference in defending against modern cyber threats.
This is a role for someone who wants to put their soul into their craft, someone hungry to learn fast, experiment boldly, and turn ambitious ideas into production-ready AI solutions.

What will you do:

* Drive innovation by combining deep security research with modern AI techniques to build impactful, customer-facing security capabilities.
* Build and refine intelligent generative AI agents that drive automated cybersecurity reasoning, investigation workflows, and threat analysis.
* Extend and enhance our next-generation AI antivirus engine by designing new feature representations, building file parsers, and developing ML models end-to-end.
* Engineer and implement core parser and model components in C++ and Python to seamlessly integrate into the Cynet Endpoint Agent and platform infrastructure.
* Use Cynet’s ML experimentation pipelines to run experiments, optimize performance, and deliver production-ready detection models.
* Serve as the cybersecurity expert within the Data Science team, guiding threat modeling, malware understanding, and security-driven AI design decisions.

About Us:
Cynet is a leader in threat detection and response, designed to simplify security for organizations of all sizes. Our mission is to empower lean security teams and their partners with an AI-powered, unified platform that autonomously detects, protects, and responds to threats - backed by 24×7 security experts. With a Partner First mindset , we focus on helping customers and partners stay protected, operate confidently, and achieve their goals. Our vision is to give every organization true cybersecurity peace of mind, providing fast, accurate protection without the noise or complexity.
This role follows a hybrid work model in countries where Cynet has offices (Israel, USA), while being fully remote in England, Poland, Italy, and Germany.

We are looking for a Senior AI Software Engineer to help build and evolve AI-powered cybersecurity products that protect customers at global scale. In this role, you will design and implement intelligent systems leveraging AI agents and large language models (LLMs), partnering across engineering, security, and product teams to deliver secure, reliable, and responsible solutions.
This role requires strong software engineering fundamentals, hands-on experience building AI-driven systems, and a passion for applying cutting-edge AI technologies to solve complex security challenges.
Why Join Us
Youll be part of the Office of the CTO of our company Security, working on innovative, high-impact security products powered by AI that shape the future of cybersecurity. We foster a collaborative and inclusive culture that values a growth mindset, technical excellence, and continuous innovation.
Responsibilities
Design, develop, and maintain cutting-edge AI technologies and products within the Office of the CTO, from early prototypes to production-grade systems.
Build and evolve AI agent-based architectures, including multi-agent workflows and tool-using agents.
Apply advanced LLM design patterns to improve accuracy, robustness, and safety of LLM-powered systems, including prompt engineering, flow engineering, Retrieval-Augmented Generation (RAG), self-review, ReAct, and guardrails.
Write high-quality, secure, and maintainable code primarily in Python, following modern software engineering best practices.
Collaborate with cross-functional teams, including product, research, and security, to define requirements and deliver end-to-end AI solutions.
Identify and resolve reliability, performance, and security issues in AI-enabled services.
Contribute to architecture and design reviews, ensuring solutions meet security, privacy, compliance, and responsible AI requirements.
Mentor other engineers and contribute to a culture of engineering excellence and continuous learning.