לוח משרות דרושים הייטק AI עבודה היברידית

We are seeking an AI Engineer to design, build, and deploy AI-powered capabilities within our product.
This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.
The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure.
transforming AI technologies into practical applications.
Responsibilities:
Build applications powered by machine learning and large language models (LLMs).
Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.
Integrate AI functionality into backend services and product workflows.
Design and implement retrieval pipelines, embedding pipelines, and inference workflows.
Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.
Create scalable AI architectures capable of handling production workloads.
Package and deploy AI models as production services.
Optimize inference performance, scalability, and latency.
Monitor AI services to ensure reliability and performance.
Develop backend services and APIs that expose AI capabilities.
Integrate AI systems with databases, internal services, and external APIs.
Contribute to system architecture and microservices design.
Implement logging, metrics, and observability for AI systems.
Track model performance and system reliability in production environments.
Work closely with product managers, engineers, and data scientists.

we are looking for a AI Team Lead.
As our AI Team Lead, you will sit at the intersection of cutting-edge research and production engineering, guiding a high-performing team of Data Scientists and Engineers. This is a deeply hands-on leadership role where you will drive the end-to-end lifecycle-from initial research and PyTorch training to deploying sophisticated multi-modal AI (Text, Image, Audio, and Video) in high-throughput environments. Join us in building the future of responsible AI adoption and digital integrity.
Responsibilities:
Manage and grow a high-performing team of AI researchers and engineers, fostering technical excellence.
Drive the design and training of multimodal models applications (Text, Image, Audio, Video) using PyTorch.
Own the AI roadmap from initial concept to scalable, high-throughput production.
Partner with Product, Backend, and Security teams to integrate AI solutions globally.
Stay at the forefront of GenAI/LLM research to continuously improve our detection engines.

We're looking for a senior AI Engineer with a strong backend background and deep experience building agentic AI systems to join our growing team.
Responsibilities:
Own the development of end-to-end AI agents, including both customer-facing agents and deep background agents. This includes designing agent architectures, building and maintaining agent tools, constructing and iterating on prompts, and continuously evaluating, operating, and improving the agent infrastructure in production.
Integrate large language models (LLMs) into production environments to enable autonomous task handling and decision-making.
Collaborate closely with engineering, product, and security teams to turn ambiguous problems and AI research into reliable, production-grade capabilities.

We move fast, leverage AI in every work aspect, and are customer obsessed, as we continue building a product that helps our customers grow better with CLG, generate value daily, and save time.
About the role
Were looking for an execution-focused Product Manager to own initiatives end-to-end within a complex B2B SaaS platform.
The role combines product thinking with hands-on execution: from writing requirements and aligning teams, to prototyping and occasionally shipping changes directly to production using AI-assisted tools.
This role is designed for people who want responsibility, speed, and the ability to build, not just plan.
What Youll Do
Own product initiatives from kickoff through post-release.
Translate customer and internal input into clear, actionable product requirements.
Align engineering, design, and stakeholders on scope, tradeoffs, implementation details and delivery decisions.
Own feature rollout, enablement, and activation with CS.
Build deep understanding of customer personas, use cases, and desired outcomes by running direct customer conversations, joining onboarding and support sessions.
Take hands-on ownership of features post-launch, becoming the internal product SME through customer adoption and successful use cases.
Build & ship smaller product changes directly when needed using Cursor and AI-assisted tools (weve shipped 80+ features without developer involvement, to date).

We are looking for an AI Enablement Tech Lead to lead the development of AI-native data capabilities and drive the adoption of AI across analytics workflows.
This role is part of the Analytics & AI Enablement group within the data department and is responsible for establishing the foundational data and AI capabilities that support advanced use cases, including chat with data, autonomous analytics, and AI-driven decision-making.
You will act as a technical and strategic bridge between data, engineering, and AI platform teams - owning the design of AI-ready data layers, and taking a significant part in the specification and orchestration of data-ready agent solutions and analytical workflows, from ideation to production.
You are a hands-on builder and a transformation leader, with proven experience delivering AI solutions and a strong foundation in data and analytics.
Hybrid
Full-time
What youll do: 
Define and build AI-ready data foundations, including semantic layers optimized for LLM and AI consumption
Design and standardize AI-native analytics workflows, combining data modeling, LLMs, and orchestration frameworks
Partner with Data Engineering and AI platform teams to shape infrastructure, tooling, and data interfaces for AI use
Drive experimentation with new AI capabilities and rapidly iterate from POC to scalable solutions
Establish best practices for AI usage in analytics, including prompt design, evaluation, monitoring, and governance
Act as a technical leader and mentor, driving AI knowledge and adoption across the analytics community.

- Drive technical decisions around AI evaluation frameworks, monitoring, and observability tools
- Design, build, and deploy AI-powered solutions across yad2s products and platforms
- Work hands-on with Large Language Models (LLMs), retrieval-augmented generation (RAG), embeddings, vector databases, and prompt engineering
- Develop scalable backend services that integrate AI capabilities into production
- Collaborate closely with product, data, and engineering teams to identify high-impact AI opportunities
- Lead by example: write clean, high-quality code, set best practices, and help shape the foundation of the AI team

We are looking for a senior product manager to join our AI Unit and help shape the AI platform that powers our next generation of products.
This role focuses on the platform and ecosystem layer of AI, building the capabilities, standards, and systems that enable teams across the company to create AI-powered experiences effectively.
You will work closely with engineering, data, and product teams to define how AI capabilities are built, reused, and governed across the platform.
This is a high-impact role with broad scope. It requires strong product fundamentals, technical curiosity, and the ability to operate in an evolving space.
Job responsibilities:
Own key parts of the AI platform roadmap, balancing foundational investments with product impact
Help define reusable AI capabilities (e.g., retrieval, embeddings, scoring, agent tooling)
Contribute to shaping how we evaluate, monitor, and improve AI systems in production
Partner closely with engineering on architecture and technical tradeoffs Support the definition of governance and control mechanisms (quality, safety, cost, transparency)
Work with product teams to enable adoption of AI capabilities across the platform
Improve developer and product team experience when building AI features
Contribute to defining standards, best practices, and ways of working for AI across
What makes this role interesting:
You will work on foundational systems that impact multiple product areas
You will help shape how AI is built and used across the entire platform
You will collaborate across teams and influence both product and technical direction
You will operate in a fast-evolving domain with real opportunity to define how things should work.

Were looking for a structured, tech-savvy CX Knowledge & AI Chatbot Manager to join the CX Delivery team.
This role sits at the intersection of AI chatbot operations, knowledge management, and CX delivery. Youll primarily own and optimize Support AI Agent (chatbot) and help strengthen the knowledge and content ecosystem that powers both AI and human support.
Were looking for someone with hands-on experience in chatbot management and knowledge systems - not just general CX experience. You should be comfortable working with chatbot flows, intents, and automation logic, as well as structured Help Center or Community content.
This is not a writing-heavy role. Its an enablement role focused on connecting knowledge sources, improving automation performance, and scaling self-service intelligently. In addition to chatbot and knowledge ownership, you may also contribute to broader CX Delivery initiatives such as workflow improvements, automation projects, and operational enhancements as business needs evolve.
AI & Chatbot Management (Primary Focus):
Configure, maintain, and optimize the AI chatbot (Zendesk AI Agent)
Manage chatbot instructions, use cases, workflows, intents, and data sources
Review conversations to identify gaps, fallback patterns, and improvement opportunities
Monitor performance metrics (deflection, customer experience, CSAT/BSAT, routing accuracy)
Ensure alignment between AI logic, tone of voice, and product updates
Knowledge / Content Governance (Primary Focus):
Maintain knowledge structure and taxonomy across Help Center, Community, and AI knowledge layers
Ensure synchronization between customer-facing content, agent knowledge, and chatbot use cases
Identify content gaps using ticket trends and AI insights
Collaborate with CX and Product enablement stakeholders to maintain accuracy and clarity
Continuous Improvement & CX Delivery Support:
Turn AI and support insights into structured improvements
Support automation and workflow optimization initiatives
Contribute to scalable CX Delivery project and various, team objectives, goals and tasks as needed
​Success Looks Like:
Chatbot experiences are accurate, well-maintained, and continuously improving
AI performance improves through structured knowledge alignment
Knowledge content is unified, searchable, and up to date
Automation reduces support load while maintaining strong customer experience
CX Delivery initiatives scale efficiently and predictably.

We are looking for a Prompt Engineer to design, optimize, and continuously improve multi-turn conversational experiences across multiple product lines. This role combines linguistic creativity, AI prompt engineering, and real-world experimentation.
Youll work closely with product managers, who will provide requirements and prioritization, while you focus on crafting and iterating prompts, testing in real-world scenarios, and delivering natural, trustworthy interactions.
This role is based in Tel Aviv, with a hybrid work setup, combining in-office collaboration with remote flexibility.
Key Responsibilities:
Conversational Design and Prompting:
Design multi turn dialogue flows for text and voice agents with context awareness and memory handling. Define personalities and tone across products and agents.
Create multilingual prompt strategies and develop reusable templates and frameworks to speed development.
Continuous Testing and Improvement:
Test prompts with recordings, transcripts, and simulations before and after launch. Analyze live interactions to spot hallucinations, tone issues, dead ends, and token inefficiency.
Iterate quickly to improve quality, safety, and naturalness and use analytics and qualitative insights to measure success.
Collaboration and Delivery:
Partner with product managers on requirements and goals and work with engineers to integrate prompts within technical constraints.
Coordinate updates across multiple agents with version control for a unified experience and support compliance and privacy standards.
Documentation and Knowledge Sharing:
Maintain a prompt library with flows, system prompts, and version history and set guidelines for tone, multilingual consistency, and testing.
Share insights and learnings with the broader product and AI teams.

We are looking for an enthusiastic AI Solution Manager who is a builder at heart and a changemaker by nature. In this role, you will be the catalyst for innovation, bridging the gap between ambitious business goals and actual technical delivery.
You wont just manage tasks; you will own the solution from idea to impact. We are looking for someone with a relentless curiosity to learn new tools, a passion for automation, and the drive to revolutionize our workflows. You will partner with stakeholders to design, prioritize, and build agentic AI flows that change the way we work.
What will you do?
Design & Build (Hands-on): Actively design and configure AI agents and automated workflows using low-code/no-code platforms. You turn concepts into working prototypes.
Product Ownership: Take ownership of AI initiatives. Define the scope, manage the timeline, and prioritize tasks based on business value and potential ROI. Ensure we are building the right things.
Stakeholder Partnership: Collaborate with business leaders to identify pain points. act as a trusted advisor who understands their needs and translates them into technical reality.
Drive Innovation: Be the companys "AI Radar." Constantly explore new tools and models, bringing fresh ideas to the table and challenging the status quo to improve efficiency.
Optimization & Impact: Don't just launch and forget. Monitor the performance of your solutions, troubleshoot issues, and iterate to ensure they deliver continuous value.

we are looking for a AI Architect.
Responsibilities
1. AI Architecture & Technical Leadership
Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.