דרושים » הנדסה » AI Specialist

We are looking for a AI Automation Engineer to join our team.

We're searching for a talented and passionate technologist to implement AI driven innovation by integrating AI Agents and AI APIs in automation processes and Internal Tools. As a key member of the team, you'll play a vital role in developing and implementing innovative solutions to enhance our company's efficiency, productivity and quality. You'll leverage your expertise in artificial intelligence (AI) , automation tools, and software development to design, build, and deploy tools that streamline workflows, automate repetitive tasks, provide insightful data analysis, reduce costs and help the company scale.

Responsibilities
Work with the AI Projects Manager to research, design, and develop AI-powered solutions (e.g., chatbots, machine learning models) to automate tasks, unlock scaling opportunities and generate efficiencies across the company.
Build internal tools that automate workflows, improve data accessibility, and improve data accessibility, and facilitate collaboration within the company.
Integrate AI and internal tools seamlessly with existing systems and infrastructure to ensure smooth operation and data flow.
Write clean, maintainable, and well-documented code or automation processes, adhering to best practices and security standards.
Conduct unit tests and implement test-driven development (TDD) methodologies to ensure code quality and reliability.
Monitor and maintain deployed tools, identifying and resolving technical issues promptly.
Stay up-to-date with the latest advancements in AI, automation tools, AI APIs, and internal tool development best practices.

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 an AI Program Manager to join our team.

We're searching for a talented and passionate technologist to lead internal innovation across the entire company by implementing AI, Automation and Internal Tools. As a key member of the team, you'll play a vital role in developing and implementing innovative solutions to enhance the company's efficiency, productivity and quality. You'll leverage your expertise in artificial intelligence (AI) and project management to design, build, and deploy tools that streamline workflows, automate repetitive tasks, provide insightful data analysis, reduce costs and help the company scale.

Responsibilities
Collaborate with multiple department heads across the company to identify opportunities, implement POCs and build a roadmap of AI based automation projects and internal tools.
Research, design, and develop AI-powered solutions (e.g., chatbots, machine learning models) to automate tasks, unlock scaling opportunities and generate efficiencies across the company.
Work with the AI Automation Engineer to build internal tools that automate workflows, improve data accessibility, and facilitate collaboration within the company.
Integrate AI and internal tools seamlessly with existing systems and infrastructure to ensure smooth operation and data flow.
Maintain clear documentation, develop training materials and ensure tools and capabilities are enabled and used by potential users across the company.
Conduct ongoing training sessions to the company about internal tools, as well as general developments in the AI space.
Stay up-to-date with the latest advancements in AI, off the shelf tools, and internal tool development best practices.

We are seeking a Product Manager for AI Platform, to lead most critical evolution: the transformation to an Agentic Platform.

This role operates as a "Startup within a Startup." You will own the end-to-end AI domain, from building the underlying technical infrastructure to launching the interfaces our customers interact with.

You will drive the entire product lifecycle: bringing innovative ideas to the table, executing on early versions, and collaborating closely with internal teams and design partners to validate value. Your ultimate goal is to mature these capabilities from early concepts into core platform standards, driving mass adoption across our entire user base.

You will serve as the knowledge center for the organization, guiding how the entire platform must evolve to support the next generation of autonomous engineering.

What You Will Be Doing

Lead AI product domain from ideation to launch of customer-facing AI interfaces and agents
Design and manage AI Agents platform, enabling customers to create, manage, and run AI agents
Drive ecosystem initiatives to make the platform native to agents through API improvements, MCP integration, and agent-accessible protocols
Define strategic direction for making "AI-Native," guiding data architecture for effective AI agent interaction
Own product roadmap and prioritization, balancing immediate needs with long-term Agentic architecture investments
Advocate across product and R&D teams to integrate AI-native interfaces and drive AI-first development mindset
Identify high-impact opportunities through customer discovery and experimentation with cutting-edge AI technologies
Collaborate with engineering and design to translate AI capabilities into intuitive, trust-building user experiences
Analyze adoption metrics and feedback to optimize AI performance and increase trust in autonomous workflows
Act as company AI center of excellence, enabling Sales, Marketing, and CS teams to articulate Agentic Engineering value

As part of our ongoing innovation, were expanding our capabilities around AI-driven development and automation. The Dev AI Infra & Tools team leads this transformation - building the internal platforms and tools that empower our engineers to design, test, and deliver faster, smarter, and more securely.

Youll work hands-on with Generative AI frameworks and agents, developing the systems and integrations that change the way our engineering teams work.



Key Responsibilities
Design and build AI-driven internal tools that enhance developer productivity.
Develop and maintain the infrastructure supporting GenAI agents and automation frameworks.
Prototype and experiment rapidly, turning ideas into practical solutions.
Collaborate with DevOps, backend, and product engineers to identify and implement high-impact GenAI use cases.
Evaluate new Generative AI and agent-based technologies and integrate the most promising ones into production.
Define and track efficiency metrics to continuously improve developer velocity and experience.

we are looking for a AI Solution Engineer - Corporate Business Applications (Contractor).
As an AI Solution Engineer, youll help shape how AI-driven automations are applied across our internal systems. Youll build and operate AI agents and workflows that connect data, tools, and processes, enabling teams across the organization to work more efficiently at scale.
Youll work closely with IT and platform stakeholders, as well as teams across the company, combining AI capabilities with automation tools, APIs, and code to deliver solutions that move from experimentation to reliable, long-term operation.
What will you actually be doing?
Design and develop AI automations, agents, and agentic workflows that automate and augment internal business processes.
Develop and maintain integrations and workflows using tools like n8n, Workato, and other automation or orchestration platforms.
Write JavaScript-based logic (and Python where relevant) to extend low-code/no-code tools, integrate APIs, and orchestrate AI-driven flows.
Build scalable, secure, and reliable automations, including monitoring, logging, and guardrails for AI behavior.
Implement advanced prompting and agent patterns, such as structured outputs, tool/function calling, and RAG.
Optimize workflows using data, telemetry, and feedback to improve reliability, performance, and business impact.
Collaborate closely with the IT team to ensure solutions align with enterprise architecture, security, and compliance standards.
**Engagement will be on a contractor basis or via an employment agency

Required Al Builder - Performance
About the role (overview)
As part of our Business Technologies & AI organization, youll build and ship AI agents and workflows that drive measurable impact on our internal core business processes-and then own their performance over time.
Using our AI Gateway, Custom GPTs, and low-code/no-code tooling, youll orchestrate prebuilt actions, design robust prompts, and wire data flows across systems like Salesforce, Snowflake, Gong, ERP, and internal tools-without writing low-level API code.
You will also treat AI agents like a real workforce: defining how they are onboarded, measured, evaluated, and improved. Youll build the operating model, metrics, and evaluation solutions that keep our AI ecosystem powerful, safe, and cost-effective.
1) AI Solution Design & Development
Rapidly build, test, and deploy AI agents using the AI Gateway, Custom GPTs, and low/no-code tools.
Design scalable, secure, and reliable workflows with strong prompt patterns, evals, and canary tests.
Define new actions with Platform/Integrations when needed; ensure every agent has clear I/O, purpose, and a KPI.
2) Orchestration, Data, & Operations
Configure and chain actions; handle mapping, preprocessing, errors, retries, and safe context assembly.
Use managed auth/secrets with least-privilege access and data minimization.
Write SQL for retrieval context, routing rules, golden sets, and performance queries.
Integrate logs, BI, and admin tools into a single operational view.
3) Performance, Quality & Evaluation
Define and track core metrics: usage, adoption, accuracy, cost, time saved, revenue impact.
Build dashboards, scorecards, leaderboards, and automated alerts (health, anomalies, regressions).
Maintain evaluation frameworks and pipelines (golden sets, scenarios, automated checks).

We are hiring a Staff Data AI Lead to lead our AI initiatives.As a Staff Data AI Lead you will be responsible for leading SuperSonic organization AI integration efforts and serving as the bridge between advanced AI technologies and our business needs, implementing cutting-edge Data & AI technologies, creating AI-driven strategies and integrating innovative AI solutions across multiple platforms.
What you'll be doing
Develop and execute AI strategies aligned with business objectives
Advise leadership on AI capabilities and potential applications
Guide teams in adopting AI tools and methodologies
Ensure ethical and efficient implementation of AI technologies
Design and oversee AI-driven process improvements
Collaborate with various departments to identify AI opportunities
Stay current with the latest AI trends and advancements
Conduct AI-related training and workshops for staff
Manage AI projects from conception to implementation
Evaluate and recommend AI tools and platforms
Leading a team of AI engineers.

We are looking for an experienced AI Backend Engineer to join our fast-growing company during an exciting stage of innovation. In this role, you'll design and develop Agent and LLM-based features, engineer and optimize context and high-quality prompts, implement agentic architectures in production and evaluate and monitor applications effectively. If you're passionate about staying at the forefront of Large Language Model AI applications and collaborating with a team of experts, wed love to hear from you!

What Will You Do?
Take part in all development aspects, from design to production, of Agent and LLM-based features and applications.
Take part in all the development and planning aspects of a backend application, understanding scale, performance, observability.
Craft and optimize high-quality prompts to enhance application functionality and output quality.
Develop datasets and benchmarks to evaluate and monitor LLM-based applications effectively.
Stay up to date with state-of-the-art research in the field of Large Language Models and apply relevant advancements to improve our applications.
Collaborate closely with other team members and contribute to a culture of innovation and continuous improvement.
Mentor new team members and share your expertise to strengthen the team's collective knowledge.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.
In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.
You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.
If you enjoy working at the intersection of AI and engineering - bringing models to life in production, optimizing for performance, and building reliable systems - this role is for you!
Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models.