לוח משרות דרושים הייטק AI עבודה היברידית, לחיפוש זה נמצאו 53 משרות

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make our data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for our data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

We are looking for a Senior AI Researcher to join our foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.

In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.

You do not need prior biology experience - but you should be excited to apply your deep learning expertise to a new scientific domain.

Location: Ramat Gan, Israel (hybrid model)

What will you do?
Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
Tackle challenging modeling problems with thoughtful, principled approaches.
Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.

Were seeking a Head of AI to lead research and engineering for multimodal foundation models and reasoning‑centric systems-from prototyping to reliable, secure, production deployment. The Head of AI will manage deep learning researchers, computational biologists, immunologists and engineers and partner closely with product leaders and company leadership to convert cutting‑edge methods into high‑impact, mission‑critical capabilities.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Team Leadership & Growth
Lead, mentor, and develop deep learning researchers, computational biologists, and machine learning engineers; set a high bar for scientific rigor, code quality, and delivery.
Establish clear ownership, role definitions, and growth paths; nurture a collaborative, low‑ego culture.

Technical Strategy & Delivery
Own the AI roadmap and architecture; guide model design, evaluation, and productionization (training, serving, observability, safety).
Build scalable pipelines for transformers, multimodal fusion, and reasoning/agent frameworks; champion reproducibility, CI/CD for models, and cost‑efficient GPU/TPU utilization.

Research Integration & Innovation
Stay current with the literature; run journal clubs and technical deep dives.
Evaluate, pilot, and integrate state‑of‑the‑art methods (advanced transformers, retrieval and tool‑use agents, causal/biological reasoning) into robust systems.

Cross‑Functional Collaboration
Translate biological and clinical questions into tractable AI projects with measurable impact.
Communicate complex trade‑offs to peers and executives; align plans, risks, and milestones across functions.

Mission & Impact
Prioritize initiatives that advance patient outcomes and create cumulative platform value.
Balance speed with scientific integrity, security, and compliance.

As the AI Product Director for the core components of our AI modeling framework, you will be responsible for defining and driving its product strategy, requirements, and roadmap, as well as lead a team of product managers. By leveraging our AI capabilities and vast data assets, you will spearhead the development of a product designed to empower internal users and external customers to address real-world challenges in drug discovery and development. Partnering tightly with R&D, you will ensure alignment between product strategy, scientific priorities and business objectives. You will advocate for your product both internally and externally, and ultimately be accountable for the value and impact your product delivers.

Location: Ramat Gan, Israel (Hybrid model)

What will you do?
Establish the long term vision and strategy to advance our AI-powered analytical platform to enable our mid and long-term goals.
Responsible for defining the comprehensive roadmap and related PRDs for the analytical platform, focusing on optimizing analytical workflows, tackling predictive challenges, and enhancing model interpretability, as well as partner with business, R&D and ops to realize the roadmap.
Evangelize the product, creating understanding and alignment across key stakeholders.
Drive value creation for analytical platform users by enabling them to leverage our data assets effectively, both internally and in external collaborations.
Ensure that our analytical platform development is effectively enabling and accelerating our product, business, and therapeutic goals.

We are seeking a highly motivated and experienced LLM/ML Agentic AI Researcher to lead the technical development of our agentic AI interpretation framework. This hands-on role involves designing, building, and evaluating AI agents that interpret complex biological data.

You will be at the forefront of developing a sophisticated scientific reasoning system that leverages Large Language Models (LLMs) to provide structured, biologically-grounded explanations. Collaborating closely with immunologists, machine learning researchers, and technical leadership, you'll shape how we derive insights at a systems level, pushing the boundaries of AI in biology.

Location: Ramat Gan, Israel (Hybrid role)

What will you do?
Design, prototype, and build LLM-based agentic systems that reason over biological data, scientific literature, model outputs, and internal tools.
Develop agents capable of structured reasoning, hypothesis generation, explanation, planning, tool use, and iterative scientific analysis.
Build robust evaluation frameworks for agentic systems, including automated and human-in-the-loop evaluation pipelines.
Define and implement benchmarks, metrics, and test suites for measuring agent performance, including reasoning quality, biological grounding, factuality, robustness, reproducibility, and usefulness.
Work closely with AI researchers, computational biologists, immunologists, and product teams to translate scientific needs into measurable AI capabilities.
Create evaluation datasets and benchmark tasks that reflect real-world biological and therapeutic reasoning problems.
Analyze agent behavior, failure modes, hallucinations, tool-use errors, reasoning gaps, and grounding issues.
Contribute to the architecture of production-grade AI systems, including agent orchestration, retrieval, tool calling, memory, planning, and monitoring.
Stay up to date with the latest developments in LLMs, agentic AI, evaluation methodologies, and scientific AI systems.
Help turn research prototypes into reliable products used by internal teams and external partners.

You will join the Deployment Platform team, which puts technology directly in the hands of customers, field technicians, and partners. As an AI-Native mobile engineer, your primary development framework is Flutter (with native iOS and Android used when needed), building the mobile application central to field deployment. You are also comfortable across the full stack to ensure end-to-end feature delivery. Most importantly, you will shape the next generation of agentic installation experiences that define how industrial AI reaches the factory floor. This is a high-impact role at the intersection of mobile, IoT, and AI.
A Day In Your Life:
Design, build, and maintain high-quality, cross-platform mobile applications for iOS and Android using the core Flutter/Dart stack.
Lead the design and shipment of agentic-first workflows for guided installation, leveraging LLMs (Azure OpenAI, Gemini) to assist technicians and automate decision-making in the field.
Implement complex IoT/Hardware integration features, including NFC provisioning, AR field tools, and indoor positioning/navigation.
Contribute to backend and frontend services/APIs to ensure seamless, end-to-end feature delivery.
Architect and maintain a scalable, modular monorepo, ensuring robustness through strong state management (BLoC/RxDart) and comprehensive test coverage.
Collaborate with product and design teams to deliver exceptional UI/UX, including adaptive and RTL-aware layouts.

we are looking for a Experienced AI Software Engineer.
You are a Senior AI Software Engineer looking to join a GenAI Infrastructure team and build production-grade GenAI capabilities and the infrastructure behind them. You will be a hands-on engineer focused on AI agents, RAG pipelines, tool-calling workflows, backend services, data access layers, evaluation, observability, and reusable GenAI infrastructure used across product teams. You will not be focused solely on model research or prompt design. Instead, you will be a strong software engineer who can design, build, ship, and operate reliable AI-powered systems in production.
A Day In Your Life :
Build reusable infrastructure, SDKs, and internal frameworks for AI-powered product capabilities.
Design and implement AI agents, RAG flows, tool-calling workflows, and LLM orchestration pipelines.
Build production-grade GenAI services, APIs, and backend infrastructure.
Integrate LLM workflows with internal microservices, data platforms, vector search, and event-driven systems.
Design secure data-access patterns that enforce authorization, tenant separation, and user-level scope.
Implement evaluation, tracing, monitoring, and quality-control mechanisms for GenAI systems.
Improve latency, reliability, fallback behavior, cost efficiency, and production readiness.
Work on customer-facing AI experiences, including conversational and proactive agentic product flows.
Collaborate with backend engineers, product managers, data engineers, AI/ML engineers, and domain experts.

we are looking for a AI-Native Pod Leader.
The AI-Native Team Leader is a new kind of engineering leader at Payoneer - equal parts technical authority, people developer, and AI-first builder. Youll lead a small AI Pod that owns its problems end-to-end: from understanding the business need, through architecture and implementation, to production monitoring. There are no hand-offs, no tickets, no specs thrown over a wall. Your team builds with AI as a primary tool, ships fast, and sets the methodology for how R&D works next.
What youll do:
Lead and develop a small 3-4 engineers AI Pod, with a clear focus on their technical growth, autonomy, and delivery outcomes
Provide technical authority hands-on - code, architect, review, and ship alongside your team
Own the full delivery loop: understand the business problem, define the solution, architect it, ship it, monitor it - no one hands you a spec
Collaborate directly with Product, Design/UX, DevOps, and business stakeholders to define decision logic, risk thresholds, and success metrics - building capabilities, not features
Drive AI-native development - Claude Code, Cursor, and whatever tools give your team the most leverage; build in a day what used to take a team a week
Build the harness before you ship - evaluation frameworks, monitoring, and observability go in on day one, not after the first incident
Be accountable for overall design, architecture, code quality, and production environment across your team
Set a higher technical bar - run design reviews, champion engineering best practices, and push for continuous improvement in code quality and team craft
Define the methodology - this is early-stage work within Payoneer; you wont inherit a playbook, youll write it

We are looking for an exceptional Principal Product Manager to help build Core AI Platform-the trusted, scalable AI operating layer enabling Product, Engineering, and Business teams to adopt AI safely and effectively.
Reporting to the Senior Product Director, Core AI Platform, you will take part in translating strategy into concrete roadmaps and capabilities, and partner deeply with Engineering, Data, Architecture, Security, and business stakeholders to deliver reusable AI capabilities across .
This role is ideal for a senior, hands-on product manager, AI savvy, who combines technical depth, exceptional product sense, execution excellence, and the ability to drive adoption across complex organizations.
What you'll do:
The Core AI Platform enables three strategic outcomes: transforming how products are built, enabling every business function to redesign and automate workflows through AI, and creating agentic customer experiences across products.
You are not building isolated AI features for one product. You are building platform capabilities, reusable patterns, and product experiences that help teams across ship trusted AI faster, safer, and at scale.
Own the roadmap for one or more Core AI Platform areas.
Translate ambiguous business and technical needs into clear requirements, milestones, and measurable outcomes.
Define and deliver scalable, secure, compliant platform capabilities across AI infrastructure, orchestration, governance, evaluation, responsible AI, APIs, and reusable services.
Partner hands-on with Engineering, Data, Security, and Architecture to make practical build, buy, partner, and integrate calls in your domain.
Lead AI-native solutions that show how the platform accelerates product development, engineering productivity, and workflow automation.
Turn early solutions into reusable patterns, templates, and components teams can adopt.
Drive and track adoption of the tools and services you will build.

We are looking for a technically-grounded, visionary Product Owner to lead GenAI-powered initiatives within our B2B platform. You will stand at the intersection of cutting-edge LLM technology and enterprise-scale business impact, transforming how global financial institutions handle everything from underwriting automation to complex claims intelligence.

Key Responsibilities:
AI Roadmap & Strategy: Define and own the GenAI roadmap, identifying high-value use cases like fraud detection copilots, document intelligence, and agentic underwriting.
Backlog Excellence: Own and optimize the product backlog, translating complex AI concepts into clear user stories and acceptance criteria for engineering and data science teams.
Technical Specs & Orchestration: Read and write technical specs, API contracts, and data models. Youll work closely with Development & architecture teams
Experimental Mindset: Lead lean experiments and A/B tests to validate LLM performance, managing the balance between probabilistic AI outputs and deterministic business rules.
Stakeholder Leadership: Communicate the vision and progress transparently to global stakeholders and enterprise clients, acting as the bridge between "the possible" and "the practical".

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Key responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

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.

Were looking for a Generative AI Developer to join our forward-thinking engineering team. This role is perfect for someone with a passion for cutting-edge AI, a strong software engineering background, and the creative spark to identify and implement novel use cases within our product.
You will play a critical role in adding AI capabilities to our FinOps SaaS platform. Whether it's enhancing user workflows, automating insights, or inventing entirely new product experiences, youll have both the freedom and support to experiment and execute.
We provide a uniquely rich dataset covering the full scope of a companys cloud spend. This expansive data playground offers a powerful foundation for experimentation and insight generation, enabling the development of intelligent, value-driven features.
Responsibilities:
Lead the charge in transforming our product and preparing it for the agentic age.
Design, build, and deploy generative AI-powered features across our product.
Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs
Prototype and validate new AI use cases quickly and iterate based on internal and external feedback
Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production
Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).
Live in the future and track new innovations and paradigms in this fast evolving field and identify opportunities to integrate them into the product
Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs
Optimize model performance, inference time, and cost efficiency within AWS infrastructure.

we are looking for a Senior AI Engineer.
Responsibilities:
- Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems for cybersecurity use cases
- Architect and operate multi-agent systems in production - covering orchestration, inter-agent communication, task delegation, and failure handling at scale
- Build agent monitoring and observability pipelines, including tracing, drift and failure detection, alerting, and reliability SLA management
- Build and maintain scalable MLOps infrastructure - model serving, evaluation frameworks, experiment tracking, and CI/CD for ML
- Fine-tune and adapt foundation models on internal datasets such as network telemetry, security logs, and threat intelligence
- Establish and champion best practices for model observability, safety, and responsible AI deployment
- Stay current with the LLM/GenAI ecosystem and drive continuous improvements to the AI SDLC and AI Research cycle

Join an innovative technology company developing an AI-powered computer vision platform with real-world impact. In this role, you'll lead the design, development, and deployment of advanced AI and computer vision algorithms, taking solutions from research to production while working closely with multidisciplinary engineering teams.
Responsibilities:
Design, train, and deploy deep learning models for computer vision applications.
Develop algorithms for object detection, segmentation, tracking, and behavior analysis.
Build and optimize real-time AI solutions for edge and cloud environments.
Research, evaluate, and integrate state-of-the-art AI and computer vision technologies.
Monitor, debug, and continuously improve production ML systems.
Collaborate with Software, Product, QA, and multidisciplinary engineering teams, while mentoring other engineers.