לוח משרות דרושים הייטק AI משרה מלאה, לחיפוש זה נמצאו 270 משרות

We are building a new AI venture inside monday.com to redefine how businesses interact with their customers through next-generation conversational AI and agentic systems. Our AI doesnt just react - it plans, reasons, and acts.

Youll join a small, highly autonomous team with the agility, ownership, and pace of a startup, working alongside world-class engineers and researchers to build the next generation of conversational AI. Youll have access to large-scale real-world data, the compute and resources to pursue groundbreaking research, and the freedom to move fast while helping shape Harmonys AI vision.

What youll do

Research novel algorithms and design new deep learning architectures to advance our in-house NLP and conversational models.

Develop methods for translating customer goals into structured representations with controlled states and real-time observations.

Help design the reasoning layer that orchestrates our AI models efficiently alongside a range of LLMs, enabling each agent to adapt its policy throughout a conversation while remaining aligned with customer objectives.

Build analytical tools that trace our AI decision process across a vast corpus of conversations, providing clear visibility into their reasoning and behavior.

Collaborate closely with engineers and product teams to translate cutting-edge research into production at scale.

Proactively lead new ideas and technical initiatives.

We are seeking a Senior AI Researcher to lead post-training evaluation, red-teaming, and reinforcement learning (RL) gym audits on open-weight models. The ideal candidate will establish rigorous benchmarking methodologies, evaluate large language models (LLMs) against complex threats like Indirect Prompt Injections (IPI), and construct post-training evaluation pipelines that accurately measure realistic frontier-level security capabilities. Key Responsibilities RL Post-Training & Benchmarking: Execute post-training runs (e.g. GRPO) using mainstream open-weight generalist models against security-focused RL environments, targeting threat vectors like Indirect Prompt Injection (IPI). Reward Diagnostics & Trace Analysis - Analyze live loss curves and rollout traces to identify reward hacking, lazy policy convergence, and flawed or over/under-specified verifiers. Task & Environment Auditing: Review tasks and multi-turn environments (including tool use, web navigation, and computer use) for realism, threat model accuracy, data distribution, and dataset balance. Performance Reporting (Gym Cards): Generate comprehensive evaluation cards detailing hill-climbing performance uplift across checkpoints, failure modes, tokens/turns per rollout, and task-level success rates. Integration & Orchestration: Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings.
About us:
we are 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, our company 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. we are widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

We are looking for an AI Engineer to build the systems that drive this: AI agents that investigate vulnerabilities, generate and validate code fixes, and continuously refine their performance. In this role, youll work at the intersection of AI engineering, security automation, and rigorous evaluation to translate cutting-edge models into dependable production tools.

Responsibilities

Build and evolve production AI agent pipelines for CVE research, patch generation, validation, container image remediation, and end-to-end merge requests.

Design the agent capabilities behind those workflows: prompts, tools, model selection, context, guardrails, and integrations.

Build the feedback loops that make our systems better: tracing production runs, creating datasets, defining evals and scorers, and using results to guide iteration.

Analyze real-world performance to answer the questions that matter: Did this change improve patch success, quality, latency, or cost Can we prove it?

Operate what you build in production across Kubernetes, Argo Workflows, AWS, and GitOps.

Partner closely with Product and engineering to focus on the customer problems with the highest security impact-and ship quickly.

Were hiring an AI Growth Builder - someone who naturally operates in the AI world and is eager to use it to drive rapid growth for a consumer product. This role reflects what modern growth looks like: AI comes first, and marketing builds on top of it. Your day-to-day work is powered by AI tools, with a strong focus on marketing and user acquisition. You will create and execute marketing funnels and growth strategies using tools like Claude Code, Cursor and others.

What Youll Do

Take full responsibility for growth: lead user acquisition projects from strategy through execution, using AI as your main working environment.
Configure and run A/B tests across the marketing funnel within your scope and analyze performance to drive a continuous improvement feedback loop.
Create your own growth levers: build scrapers, automations, and custom AI workflows to solve distribution challenges.
Initiate, plan, develop, and monitor sub-products and experiences within the product without relying on developers.

we are looking for a AI Engineer.
Key Responsibilities:
Develop state-of-the-art ML applications using LLMs and computer vision
Design end-to-end web application features and AI workflows
Collaborate with co-founders on requirements and software solutions for construction
Stay current with emerging technologies

In this role, you will define and execute the GenAI GTM strategy for us in Israel and Sub-Saharan Africa.
You will be driving adoption campaigns for new and existing services including Amazon Bedrock, Kiro, Amazon Quick, Amazon SageMaker and more. You will be creating salesplays to serve your markets and enabling the local specialists, account teams and customers on new launches. You will be working directly with customers, forming trusted executive relationships and supporting customers as they move from experimentation to wide AI value creation. Youll collaborate with a broad group of people across us and act as the conduit between our customers and our product teams. Most importantly, youll make a difference by applying your expertise to our customers most critical problems.

We are looking for a hands-on Computer Vision & AI Algorithm Engineer to develop advanced imaging algorithms for a cutting-edge medical device. The role spans the full spectrum of algorithm development - from creating new solutions to improving, maintaining, validating, and integrating them into the product. The ideal candidate is curious, pragmatic, and comfortable moving between deep learning, classical computer vision, data analysis, debugging, validation, and product integration as needed. They measure success by seeing algorithms work reliably in a real-world product and enjoy collaborating across disciplines to solve the challenges that move the product forward.

Responsibilities may include the following and other duties may be assigned:
Design, develop, maintain, and continuously improve AI, computer vision and image processing algorithms for a medical imaging product.
Own the full lifecycle of algorithm development, from concept and data definition through implementation, validation, product integration, and long-term maintenance.
Use both classical computer vision methods and machine/deep learning methods to come up with solutions for various problems in the domains of image classification, segmentation and 3D modeling.
Collaborate with SW developers, biomedical engineers, product specialists and other algorithms developers to refine and enhance existing applications.
Maintain and improve algorithm robustness, performance and reliability in production environments.
Identify opportunities for innovation and design novel algorithms to address complex technical challenges.
Stay at the forefront of relevant academic research by reviewing the latest papers and evaluating their potential impact on the companys algorithmic stack.

We are hiring someone to lead product level and internal team AI end-to-end: from protocol and architecture decisions to server-side implementation to the AI logic that decides when and how our tools are used, to internal processes that improve R&D and product development efficiency. This is a hands-on position with managerial aspects, not an advisory role. You will be building hands on in parallel to building the process and managing/guiding the team.

What You Will be Doing
Own the strategy and roadmap for C2As AI strategy within R&D and AI agents specifically,
Lead the AI adoption effort technically within the product and across the organization as the company learns how to become more efficient with AI usage for R&D.
Design and build MCP servers that expose our APIs as well-described, reliably usable tools for AI clients.
Build the AI decision layer - the prompting, tool schemas, and agentic logic that let a model select the right API, pass the right parameters, and recover gracefully from errors.
Implement complete, production-grade features end to end: backend services, data models, APIs, and the AI integration on top, not prototypes.
Define how AI-accessible APIs are scoped, authenticated, and permissioned, so an agent can only ever do what it is authorized to do. Security is the product, this matters.
Build evaluation and observability for the AI layer: measure tool-selection accuracy, catch regressions, and trace agent behavior in production.
Set engineering standards and mentor others as the effort grows into a team.
Implement new features required by our cybersecurity product.

We are looking for a Senior Software Engineer to join the AI Engineering team in a role focused on embedding directly with business teams to drive AI transformation. Be at the forefront of Applied AI. This role is outward-facing: you will engage with GTM and G&A functions - Sales, Marketing, Finance, HR, Legal, Customer Success - and fundamentally alter how these teams operate with AI.

What you will be doing:
Embed with GTM and G&A teams (Sales, Marketing, Finance, HR, Legal, Procurement, Customer Success) to identify, scope, and prioritize the highest-impact AI opportunities within each function, and act as both product manager and engineer for these initiatives.
Own the full lifecycle of each solution, from requirements gathering through deployment to adoption measurement and iteration, with a focus on business outcomes.
Serve as the primary technical partner and AI advisor for business function leaders, translating their needs into engineering plans and helping them develop their own AI fluency.
Develop and deliver hands-on AI enablement and training for non-R&D teams, building their ability to use AI tools independently and effectively.
Collaborate with the team to leverage shared infrastructure (MCP servers, RAG systems, evaluation frameworks, guardrails) while feeding back requirements from the field.
Measure and report on AI adoption impact - unlocking new opportunities, process improvements, and capability gains - to build the case for continued investment and to guide prioritization.

We are looking for a Senior Software Engineer to join a strong and dynamic AI Engineering team. We are the focal point for AI initiatives in our company, striving to constantly bring innovation and leverage AI capabilities across all company teams and products.


What you will be doing:
Design, build, and maintain reusable AI capabilities - including models, tools, APIs, and platforms that power both internal and customer-facing solutions.
Develop and maintain our internal MCP server that easily and securely exposes Forters vast data stores to AI agents.
Create and implement robust evaluation frameworks and AI guardrails to safeguard Forters value and ensure model reliability.
Establish deep expertise and sustainable AI engineering practices.
Promote AI readiness and track adoption across the company to build lasting impact.
Build and optimize RAG (Retrieval-Augmented Generation) systems.
Take full ownership of projects: from gathering requirements from non-technical internal users to development, deployment, and operation.
Act as a consultant and advocate for AI engineering, helping other teams leverage the platforms and tools you build.
Partner with teams across us to accelerate AI adoption and productization efforts.

we are a fast-growing tech company in the automotive space with hubs across the US and Israel. We are disrupting the multi-trillion-dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team at our company is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal-driven. At our core, we believe every voice has value and can impact our bottom line. We are looking for an AI AppSec Engineer to join our team and make a real impact on our Secure Software Development Lifecycle! As an AI AppSec Engineer your mission will be to be the driving force behind our secure development lifecycle. You wont just find bugs; you will help build the systems that prevent them. You will have the opportunity to help navigate the "Agentic Era" by building autonomous security guardrails, securing LLM-based workflows, and empowering developers to move fast without breaking security. You will also be responsible for working closely under the AppSec Architect. This role is based out of our Tel-Aviv site and will report to the AppSec Architect

What you will be responsible for:

* Build & automate: Develop and maintain internal security tooling, automated workflows, and AI security agents.
* Code integrity: Execute secure code reviews and provide actionable remediation guidance to engineering teams.
* Vulnerability management: Lead the tracking, triaging, and reporting of security flaws across all product lines.
* Best practice advocacy: Drive the adoption of secure coding standards, partnering with R&D and DevOps teams to embed security early and often.
* Extend our D&R capabilities: Build scalable solutions to identify malicious activity, triage alerts, and investigate and remediate incidents.
* Document: Draft requirement documents for security products and innovative technologies.
The top candidate will also have:

* Endless curiosity and passion for emerging technology
* Ability to handle prioritize and execute multiple tasks simultaneously.
* Ability to work collaboratively across multiple departments.
* Fluent in English - ability to lead meetings and present.
* Strong communication and collaboration skills.

Why you should join us:

* Our global team is made up of awesome forward thinking, innovative go-getters.
* Learning and growth opportunities within a fast-paced tech startup environment.
* Clear career advancement path for strong performers.
* We are committed to setting each other up for success. As a member of our team, you will work within an environment that encourages growth, initiative taking and continuous mutual feedback in order to reach your full potential.
* And of course, Wolt+ and lots of yummy treats in the kitchen:-) Does this sound like a perfect position for you or a friend? apply here.

Build the agent runtime and the LLM application layer that powers Agents - the ai-gateway that routes across Anthropic, OpenAI, and our own served models, plus tools, MCP, deep-research orchestration, and the App Builder codegen loop. You will turn frontier and owned models into product features people actually depend on.

We are looking for an AI (vision) Researcher.

As part of the team you will:

Develop novel solutions for retinal screening, spearheading healthcare accessibility.

Help prevent blindness worldwide.

Join a leading company with unique FDA approved products.

Learn from top ML researchers in the field.

As a AI-Data Engineer, youll take a leading role in building the foundation of our companys Agentic Exposure Management platform: the source of truth that tells a security team what they have, whats actually risky and why, how to fix it, and who is responsible.
Enterprises run their security across a sprawl of cloud and on-prem tools. Making sense of that sprawl is the heart of what we do. Were building a complex data fabric that reconciles data from a hundred different sources, applies sophisticated transformation and enrichment, and turns partial, uncertain signal into one trustworthy model of an organizations real exposure.
Key Responsibilities:
Model the security graph. Design an ontology that spans both the modern cloud and the classical on-prem world, abstract enough to absorb 100+ different integrations under one model, yet rich enough to carry everything needed for decision making. Decide whats an entity, whats an edge, and whats a denormalized attribute, across millions of assets and finding rows.
Own asset identity engineering and reconciliation. Upstream identifiers are uncertain and volatile. Engineer deterministic identity resolution for assets and findings arriving from different vendors.
Build LLM-based and agentic pipelines for data classification, entity extraction, and enrichment, optimizing for cost, latency, and precision in production.
Build the integration factory. Stand up a scalable integration platform that drives down time-to-integration.
Build and maintain complex ETL pipelines handling millions of records: incremental sync, complex correlation, and data quality observability and monitoring.