לוח משרות דרושים הייטק AI בשרון

Were looking for a Director of AI Product Management to lead AI Assistant, MCP Server, and the evolution of agentic capabilities across the platform. This is a unique opportunity to shape how developers and organizations build, secure, and deliver software with the help of intelligent, autonomous experiences.
As a Director of AI Product Management , you will...
Define and drive the AI strategy for platform, focusing on assistant capabilities, model integration, and developer intelligence.
Lead and mentor a team of AI-focused product managers, empowering them to deliver transformative experiences across products.
Own the vision, roadmap, and execution for AI Assistant, MCP Server, and agentic experiences.
Partner with engineering, data, and design teams to build production-ready AI systems, integrating LLMs and reasoning models into developer workflows.
Shape the AI platform architecture - ensuring context awareness, privacy, and responsible model usage across all environments.
Collaborate with Go-To-Market and Customer Success teams to identify high-impact AI use cases that drive adoption, productivity, and differentiation.
Establish a culture of experimentation and measurement - defining metrics for AI engagement, success rate, and business impact.
Stay ahead of industry trends in LLMs, AI agents, and DevOps automation, bringing fresh thinking into platform vision.
Collaborate with technical teams, business stakeholders, and cross-functional product leaders to deliver a unified development platform.

We are seeking an experienced, hands-on Senior AI Engineer to join the Generative AI applications Platform group and lead the backend implementation and architecture of AI/LLM solutions - from agent graphs and tooling to RAG, streaming, and production deployment.
As a Senior ML Engineer you will
Design and own agent architectures - Build and evolve graph-based agent workflows (multi-node LLM flows, tool execution, routing, human-in-the-loop review gates) using LangGraph, with clear state schemas, checkpointing, and streaming to production.
Turn product and user needs into backend AI - Work with Engineers, Product, and Analysts to translate business problems into technical requirements and implementations, including agent types, tools, RAG pipelines, and configuration-driven behavior.
Design, develop, and deploy GenAI capabilities end-to-end - LangChain tools and integrations, RAG (retrievers, vector stores, agentic flows), structured outputs, and APIs for chat, Copilot-style integrations, and MCP.
Raise the bar on quality and reliability - Establish patterns for observability (e.g., LangSmith), error handling, content safety, bounded autonomy (tool schemas, review workflows), and evaluation systems so that AI behavior is predictable and auditable.
Mentor and align the team - Provide technical guidance on LLM backend architecture and LangGraph/LangChain best practices so the team can iterate quickly and safely.

Join CIO Architect team and shape the future of AI! We're seeking a hands-on AI Solutions Lead to lead the development and implementation of enterprise-wide AI applications. In this pivotal role, you'll evaluate and deliver cutting-edge AI solutions to employees and teams across the organization. You'll spearhead AI solution projects from initial concept and requirements gathering through execution and widespread adoption, serving as the central point of contact between business, IT, and Data teams. You'll also stay at the forefront of the latest AI technologies.
As an AI Solutions specialist (CIO Group) you will
Collaborate with cross-functional teams to diagnose challenges and opportunities where GenAI and AI Agent can provide real, measurable value.
Lead the lifecycle of GenAI-driven applications and Autonomous Agents, transitioning rapidly from initial concept and technical feasibility to full enterprise-grade production roll-outs.
Conduct technical audits of emerging AI technologies, leading "Build vs. Buy" analyses to ensure global scalability, security, and measurable value to the organization.
Run training and enablement sessions for both technical and non-technical teams, fostering a culture of AI literacy and ensuring the organization can leverage new tools effectively.
Build and evolve the Enterprise AI technology stack, continuously scouting and integrating next-generation platforms, LLM orchestration tools, and agentic frameworks.
Serve as the primary technical liaison between IS, IT, Legal, and Data teams to ensure AI solutions are securely integrated and compliant with enterprise standards.
Own the long-term roadmap and administration of enterprise AI platforms, driving continuous solution adoption, impact measurement, and performance optimization across the organization.

What We're Looking For
Role Overview: We are developing Ask our company - a high-load financial analysis system based on Large Language Models. The architecture is built on complex multi-agent orchestration using LangGraph, FastAPI, and Elasticsearch.
We are looking for a Senior Backend Engineer specialized in Generative AI to design agent workflows, optimize interactions with models (OpenAI, AWS Bedrock), and ensure the reliability of non-deterministic systems in production.
Tech Stack: Python (Asyncio), FastAPI, LangChain, LangGraph, Pydantic, Elasticsearch, AWS Bedrock / OpenAI API, LangSmith.
What You'll Do
Agent Architecture: Design and implement complex agent orchestration logic using LangGraph. You will define state management, conditional routing, and error handling within the agent graph.
Tool Engineering: Build and optimize the tool layer (function calling) that allows LLMs to interact with internal financial APIs and databases accurately.
Performance Optimization:
-Reduce end-to-end latency through asynchronous processing and streaming (SSE).
-Implement semantic caching strategies to minimize API costs and response time.
-Optimize token usage without sacrificing answer quality.
Observability & Evaluation: Implement automated evaluation pipelines using LangSmith. You will be responsible for setting up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment.
Advanced RAG: Refine retrieval strategies. Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion to feed the most relevant context to the model.

We are looking for a Knowledge & AI Enablement Manager with proven experience in Knowledge Management and AI driven systems to design, build, and own the complete Knowledge Lifecycle for Technical Support.
This role defines how operational knowledge is created, governed, maintained, and embedded into daily Support workflows, while ensuring it is AI ready and serves as a trusted, high quality input for AI models across the organization.
Key Responsibilities:
Knowledge Lifecycle Ownership:
Own and build the end-to-end Knowledge Lifecycle for Support, from case-driven knowledge creation through continuous improvement and reuse
Define how knowledge is captured from cases, incidents, and escalations and transformed into structured, reusable, high-impact assets
Establish governance models for knowledge quality, validation, ownership, versioning, and ongoing maintenance
Design and operationalize workflows that embed knowledge creation, review, and updates into daily Support activitie
Define and implement a RACI model for knowledge creation, review, approval, and maintenance
Knowledge and AI Readiness:
Own KM platform configuration, Search and analytics tooling, taxonomy, publishing workflows, and integration with case management and AI retrieval pipelines
Define and enforce standards that ensure Support knowledge is structured, tagged, and maintained to be fully consumable by AI systems such as LLMs, RAG pipelines, semantic search, automation, and recommendation engines
Partner closely with Data, AI, and Engineering teams to align knowledge models, structure, and lifecycle with AI consumption requirements and future AI roadmaps
Act as the primary owner of the Support knowledge layer that feeds AI, ensuring consistency, reliability, and scalability
Measurement, Feedback, and Adoption
Define, track, and continuously improve KPIs including knowledge coverage, freshness, reuse, case deflection, and measurable AI performance impact
Establish feedback loops that surface insights from AI usage and knowledge gaps back to Support Engineers, driving better case handling and higher quality knowledge creation
Lead change management initiatives to drive adoption, accountability, and consistent knowledge behaviors across global Support teams.

We are looking for an experienced and dynamic Team Lead to manage a talented group of frontend & backend engineers, qa testers and devops. In this role, you will oversee the design , development and delivery of versions of our software to our biggest customer, ensuring that it meets the highest standards of quality and efficiency.
Additionally, you will collaborate closely with stakeholders in the customer team and within the organization, requiring strong communication and leadership skills.
Key Responsibilities:
Lead, mentor, and manage a hybrid team (Onshore & Offshore) of 10 engineers (frontend, backend, quality, devops), fostering a collaborative and high-performance culture.
Oversee our AI-first transformation in your team- moving all coders to do 100% vibe coding
Collaborate with product owners, QA, DevOps, and other team members to deliver high-quality software solutions within an Agile framework.
Ensure the teams not only develop features but also write comprehensive automation tests to validate and cover their work, ensuring high quality and stability.
Ensure designs and implementations align with technical specifications, industry standards, and best practices.
Promote continuous improvement by exploring and adopting new technologies and methodologies.
Provide support for customer and delivery teams in successfully implementing projects based on the platform.
Contribute to all phases of the development lifecycle, from design through deployment to maintenance.
Write well-structured, testable, and efficient code when needed.

?Full-Stack Developer & AI Solutions BOA Ideas builds complex e-commerce platforms, applications, and system integrations that power real businesses. We’re Shopify experts, application developers, and integration specialists in third-party system integrations. We love connecting systems almost as much as we love connecting with our clients. For nearly two decades, we’ve been solving technical challenges at scale — and we’re constantly evolving how we build.
We’re looking for a senior Full-Stack Developer who lives and breathes AI-powered solutions as part of their professional craft — someone who sees it as part of how they work, not just an occasional tool or feature. Someone who uses AI as part of how they think— and knows how to turn AI capabilities into real, scalable production systems. Building exceptional systems is the job — AI is part of how you do it better. If you're all about taking ownership of high-impact technical projects and help shape development standards within a sharp, energetic team — this opportunity at BOA might be the perfect fit.
What You’ll Do
* Lead development of complex web and e-commerce systems and digital platforms (frontend and backend)
* Design scalable backend architecture, APIs, and integrations - Turn complex designs into fully functional, scalable Shopify and Craft CMS solutions
* deeply familiar with AI tools and uses them as part of your everyday workflow — from coding and refactoring to automation and solution design
* Identify practical opportunities to implement AI features in a way that’s stable, secure, and scalable
* Turn product and design requirements into clean, production-ready code
* Write clean, high-quality code that performs well and scales smoothly
* Set up and maintain smart testing, CI/CD, and deployment processes
* Work closely with Project Managers, Customer Success, Webmasters, leadership and other developers to keep projects moving forward
* Mentor and support team members and contribute to improving development practices
* Look for better, smarter ways to do things — whether that’s improving code structure, tools, or overall architecture

we are the global leader in live IP-video solutions, transforming live video into greater value. We are seeking a results-oriented AI Enabler to lead our company's AI adoption journey. In this role, you will be the bridge between cutting-edge AI innovation capabilities and our business goals, driving the operationalization of AI across the organization, from PoC to production while ensuring maximum business value and maintaining our competitive edge. Responsibilities
* Lead end-to-end AI initiatives, from identifying business needs and selecting solutions to implementation, adoption, and impact measurement.
* Act as the bridge between business units and technology, translating business requirements into scalable AI solutions.
* Identify, prioritize, and manage AI use cases across departments based on value and feasibility.
* Define and track KPIs and ROI for deployed AI solutions.
* Drive AI literacy through training sessions and hands-on guidance.
* Partner with IT, Security, and Legal to evaluate and approve AI tools, ensuring compliance with data privacy, GDPR, and security standards.
* Stay up to date with the AI ecosystem and engage with relevant vendors and partners.

DRS RADA is a global pioneer of RADAR systems for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance. Join Our Team as a Employee Productivity & GenAI Expert at DRS RADA Technologies! Lead how we use Microsoft 365, Azure and GenAI (assistants, copilots, agents, coding assistants like Tabnine, and automations) to improve employee productivity across the company. Key Responsibilities
* Own the GenAI & productivity strategy in a Microsoft-based environment (Azure, M365, Teams, Copilots).
* Identify and deliver high-impact use cases and automations across business functions.
* Implement and manage GenAI assistants, copilots, agents and coding assistants
* Drive adoption, training and best practices for employees and managers.
* Track usage and impact KPIs and continuously improve tools and workflows.

A new type of finance role designed for an AI-driven organization. You will combine strong FP&A fundamentals with curiosity for GenAI tools, modern analytics, and SaaS monetization. Working closely with AI leaders, product teams, and business stakeholders, you will help translate innovation into financial insights while contributing to core financial execution.

What will your job look like?
Support planning, forecasting, and performance analysis for Data & GenAI initiatives
Build financial models for AI solutions, SaaS offerings, and data-driven business cases
Analyze monetization approaches for GenAI-driven capabilities and internal transformation programs
Design and track KPIs measuring efficiency, productivity, and value from AI adoption
Partner closely with product, engineering, and AI leaders to translate roadmaps into financial narratives
Use GenAI and analytics tools to streamline reporting and improve decision-making workflows
Maintain ownership of core FP&A deliverables while supporting strategic decision-making

We are seeking a highly skilled and visionary Lead Data Scientist with deep expertise in Generative AI to lead high-impact initiatives at the frontier of AI innovation. This role requires a unique blend of advanced technical skills, domain specialization, leadership ability, and a passion for delivering real-world impact. You will guide a small team of talented data scientists and work collaboratively across engineering and product teams to design, build, and deploy intelligent, domain-specific multi-agent systems.

What will your job look like?
Lead the design of complex, domain-specialized multi-agent Generative AI systems.
Provide technical mentorship and leadership to a team of 3-4 data scientists.
Drive hands-on research and rapid prototyping in areas including LLM fine-tuning, prompt engineering, agentic workflows, and self-improving systems.
Collaborate with product managers, engineers, and domain experts to identify opportunities and deliver AI-driven features and products.
Evaluate and integrate state-of-the-art models and tools from the GenAI ecosystem, including open-source and proprietary solutions.
Translate research outcomes into actionable product features and influence AI strategy and roadmap.
Maintain high standards for scientific rigor and data integrity throughout the development lifecycle.

In this role, you will be a key contributor to the design and implementation of AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.

You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of NPU embedded solutions, actively promoting AI capabilities to the customers.

What will you do:

Own and design key components of the AI Graph Compiler software stack for NPU-based systems.

Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.

Collaborate on HW-SW co-design, influencing NPU architecture.

Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.

Mentor junior engineers and contribute to technical best practices.

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.

Lead and mentor a team of software engineers developing Sensing AI SDK. Architect and implement high-performance sensing SW components for AI, vision, Audio and voice optimized for vectorize SIMD execution. Collaborate with compiler and DevOps teams to ensure efficient development and deployment. Drive technical excellence through code reviews, design discussions, and continuous improvement. Own the SDK roadmap, planning, and delivery cycles. Engage with customers to enable successful pre-sale processes, support integration and gather feedback.