לוח משרות דרושים AI Engineer

Required xEngineer (ai-native software engineer)
makes it possible for anyone to succeed online. since 2006, weve grown to around 5,500 employees in 22 countries, launched over 40 products, and serve over 243 million users and their visitors worldwide. here, we push you to innovate, evolve in non-traditional ways, and collaborate. we operate in small teams that work closely together at a high level.
although were already industry leaders in web creation and business, our work is nowhere near done. our goal is to become the main engine of the internet so we can create a more open web for all.
we're proud to be an equal opportunity employer. the company was built around the idea that everyone has the right to be successful, online. this same vision defines us as an employer: creating a work environment where everyone is welcome, and anyone has the right to succeed.
as an xEngineer, youll combine deep technical expertise with system -level thinking and product ownership, applying ai across the development lifecycle to build impactful systems, make thoughtful architectural decisions, and drive technical excellence from idea to production. in your day-to-day, you will:
design and own end-to-end systems and features that serve millions of users, taking responsibility across stack boundaries - from product flows and User Experience to apis, data models, and production systems
apply ai-powered tools and workflows across planning, design, implementation, testing, debugging, and refactoring
work with modern technologies and platforms (e.g., typescript, React, Node.js, JAVA, cloud, and ci/cd), continuously evolving your toolkit with ai-powered tools
lead architectural thinking by making thoughtful trade-offs around scalability, reliability, security, performance, and maintainability
collaborate closely with product managers, designers, and engineers to shape solutions while ensuring production quality, observability, and long-term system health
at the company, we believe our best work happens together. our work model is fully in person, with 5 days a week from our office. flexibility remains a core value at the company and special requests are handled thoughtfully at the team level.
we are engineering at the company - a team of ai-native xengineers with deep expertise in frontend, backend, or mobile, who use ai support to take ownership over projects end-to-end. we work in a fast-paced, dynamic development environment with autonomous teams that never compromise high quality standards. as ai increasingly generates production code, we dedicate more and more of our time developing the skills we believe are critical for today and tomorrow: system design, architecture, scalability, reliability, and security.

as an Agentic Pentest Director. Leading the development of agentic AI-driven penetration testing capabilities, focused on enabling autonomous security validation across modern software applications and infrastructure.

What Youll Be Doing

Become a company leader in the new product pillars that fall under your scope
Build a high-performing core engineering group by hiring top talent and fostering a culture of excellence, ownership, and collaboration
Drive the planning, execution, and delivery of key projects that impact the foundation of our product
Collaborate closely with product, architecture, security, product marketing, and other engineering teams to align technical vision and execution
Mentor and develop engineers, providing guidance and support for their growth
Help us continuously improve by bringing strategic thinking, hands-on leadership, and an agile mindset

Were looking for a highly technical and visionary Team Lead to join our Backend department and spearhead our Agentic Pen Tests initiative. This is a high-impact role where youll merge AI innovation with advanced Cybersecurity, working with cross-functional teams to shape the future of OX

What Youll Be Doing

Lead and scale a global backend team dedicated to developing cutting-edge Agentic Pen Testing capabilities.
Architect and build robust, scalable systems using Node.js to support autonomous security agents.
Collaborate closely with Product, R&D, and customers to define the roadmap for this new, innovative domain.
Drive technical excellence by setting high standards for code quality, security, and AI integration.
Foster a collaborative environment that encourages proactive problem-solving and rapid innovation in the AI-Cyber space.
AI-First Mentality: Integrate AI tools and workflows into the daily development lifecycle (e.g., AI-assisted coding, automated testing, and prompt-driven prototyping) to act as a force multiplier for the team.

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.

Were seeking a visionary Team Lead to lead a AI & backend-focused team building our next-generation Generative AI Platform. This platform will empower cross-functional teams across our company to design and deploy AI-driven solutions, leveraging cutting-edge advancements in generative AI, cloud-native architectures, and rapid innovation cycles.
In this role, youll manage a high-performing backend team responsible for building scalable microservices and cloud-based infrastructure, while integrating advanced AI capabilities such as evaluation frameworks, RAG pipelines, knowledge base management, embeddings, LLMs, chatbot assistants, and agent orchestration.
What Youll Do
Lead and mentor a backend engineering team developing a scalable, cloud-native AI platform. Youll foster a culture of technical excellence, collaboration, and ownership while ensuring delivery of robust, production-grade systems.
Define the technical direction and architecture for backend services, focusing on microservices, distributed systems, and AWS-based infrastructure to support AI-driven applications.
Integrate cutting-edge AI capabilities into the platform, including RAG pipelines, embeddings, LLM orchestration, and evaluation frameworks, ensuring performance, scalability, and security.
Collaborate with product and engineering teams to translate business needs into backend solutions that enable AI-agent use cases and accelerate innovation across the organization.
Drive agile processes and best practices, leveraging tools like Jira to manage sprints, track progress, and continuously improve team efficiency and delivery quality.
Scale the team strategically, hiring and onboarding top talent while mentoring future leaders to support the growth of the Gen AI Platform group.

Were looking for product-minded engineers who are excited about developer tools, SDLC improvements and AI in general to help us quickly define and ship features and tools that make all Datadog customers 10x developers.
What Youll Do:
Work on agents, prompts, evals, MCPs and direct agent tools from ideation to productization, for allowing Datadog to help companies and developers to maximize the benefit of their integration with Datadog
Help conceptualize and build innovative User flows and experiences within Datadogs user space and different extensions
Prototype and see what works well in the real world, iterate closely with our users, and then ship
Follow the latest research on LLM prompt optimization, agents, and code editing.
Support other Datadog product teams to help them build and productionize their developer-focused AI Workflows. For example, youll work with the Live Debugger team to create an agentic production debugging experience, delivering on the vision of one click to reproduce for production errors.

Were seeking a tech-savvy Product Manager to lead one of our cross-functional squads. In this role, you will drive the development and success of our product, shaping solutions that enhance efficiency and automation for IT teams worldwide.

As the Product Manager, you will own the product vision and roadmap, turning complex challenges into intuitive, impactful solutions. Youll collaborate with engineering, design, and business stakeholders to deliver innovative features that empower thousands of global customers and shape the future of AI-powered IT Service Management.



Responsibilities

Lead a cross-functional squad to own and deliver AI-driven product initiatives end-to-end, from discovery to launch and adoption.
Stay at the forefront of AI technology and trends, bringing innovative capabilities into product in a practical, customer-focused way.
Partner closely with Product Design to deliver best-in-class AI experiences that are intuitive, trustworthy, and drive adoption.
Define and prioritize product requirements by combining user feedback, market trends, data insights, and stakeholder input.
Drive data-driven decision making by defining success metrics and using product analytics to evaluate impact, adoption, and customer value.
Monitor and continuously improve AI performance over time, including quality, accuracy, latency, reliability, and user trust, ensuring consistent value at scale.
Collaborate with internal teams (engineering, analytics, customer revenue, and marketing) to ensure successful execution and alignment with business goals.

As an Integration Specialist , you will be the technical "glue" connecting our ITSM platform to the worlds leading cloud and IT ecosystems.

This is a unique, high-visibility role for someone who wants to combine deep technical work (APIs, AI-coding, and Workato) with a strategic, client-facing edge. Youll build the automations, train our teams to sell them, and jump on calls to prove their value to global customers.

Key Responsibilities

Build & Automate: Design and deploy API-based integrations between and platforms like AWS, Azure, Security tools, Asset management solutions, and more using our Agentic AI tools and low-code tools (Workato).
Technical Sales Support: Join discovery calls with prospective customers to understand their technical environment and demonstrate how our integrations solve their business pains.
Internal Enablement: Act as the subject matter expert by training internal sales and success teams on how to effectively position and "sell" our technical capabilities.
Documentation: Work with our technical writer to create clear technical blueprints and "how-to" guides for both internal implementation and customer-facing use.

We are seeking a highly skilled AI Application Team Lead to build and lead a team responsible for developing, running, and optimizing large-scale AI workloads on AI hardware platform. This role focuses on benchmarking state-of-the-art models (e.g., LLaMA, DeepSeek), executing MLPerf suites, analyzing system-level performance, and driving cross-stack optimizations across hardware, runtime, and software frameworks.

The ideal candidate combines strong technical depth in AI/ML systems, hands-on experience with LLM workloads, and leadership capability to guide a high-performance engineering team.

We are looking for a Senior AI Engineer to join our Cybersecurity team in Tel Aviv. You will design, build, and productionize LLM-powered applications, multi-agent systems, and MLOps infrastructure that power our company's next-generation cybersecurity capabilities. This is a high-impact, hands-on role at the intersection of applied AI, agentic systems, and network securit
What You'll Do
Design and develop LLM-powered security features and internal AI tools, including RAG pipelines, multi-agent workflows, and prompt-engineered systems tailored for cybersecurity use cases
Architect and operate multi-agent systems in production - including agent orchestration, inter-agent communication, task delegation, and failure handling at scale
Build robust agent monitoring and observability pipelines: tracing agent execution, detecting drift or failure, alerting on anomalous behavior, and maintaining agent reliability SLAs
Build and maintain scalable MLOps infrastructure: model serving, evaluation frameworks, experiment tracking, and CI/CD for ML models
Work with internal datasets (network telemetry, security logs, threat intelligence) to fine-tune and adapt foundation models for domain-specific detection and response tasks
Partner with the Cybersecurity, R&D, and infrastructure teams to define AI-driven security features and deliver them end-to-end
Establish best practices for model observability, safety, and responsible AI deployment within the organization
Stay current with the fast-moving LLM/GenAI and agentic AI ecosystem and evaluate emerging frameworks, models, and tools for adoption.

looking for an R&D Operations Manager to be the operational backbone of our Product and Engineering organization. You'll own how we plan, build, and ship designing processes, leading strategic projects, driving automations and AI-powered workflows, and ensuring every team is aligned and moving fast. You'll be the connective glue across Product, Engineering, Design, CS, and GTM - the person who creates order from chaos and measurably increases our velocity.

Responsibilities

Lead Strategic Projects & Planning Own quarterly planning cycles, roadmap governance, and the most critical cross-functional initiatives end-to-end. Ensure 100% traceability between business goals and what we build. You don't just facilitate - you drive outcomes.
Increase Product & Dev Velocity Design and enforce processes that make squads ship faster. Identify bottlenecks, streamline workflows, and measure the impact. If it slows us down, you fix it.
Jira Governance & Dev KPIs Full ownership of Jira - boards, workflows, automations, hygiene, and reporting across all squads. Build and maintain dashboards for velocity, cycle time, throughput, and release predictability. You're self-sufficient - no engineering help needed.
Automations & AI-Powered Workflows Automate manual toil across the product org. Operationalize AI tool adoption. Eliminate repetitive work so PMs and engineers focus on high-value output, not process overhead.
Cross-Functional Alignment & Enablement Be the connective tissue between Product, Engineering, Design, Data, CS, GTM (including PMM, Professional Services, and Pricing), and Finance. Own release coordination and CS enablement - zero surprise launches, ever.
Tooling, Analytics & Knowledge Management Own the product tool stack (Jira, PostHog, Notion, AI tools) and the budget for product tools and operations - drive ROI through smart vendor selection and consolidation. Ensure PMs have self-serve access to data. Maintain a centralized knowledge base as the single source of truth.

we are looking for a AI Security Engineer.
As AI capabilities accelerate across the bank, we need an engineer to design and enforce safe AI usage-protecting customer data, preserving model integrity, and meeting our regulatory obligations. You'll be the architect of guardrails, tooling, and policies that make AI both secure and useful for product and internal teams. This isn't about slowing things down; it's about building the trust layer that lets innovation move fast without breaking things.
What Youll Actually Be Doing:
Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
Implement data minimization controls for GenAI/RAG workloads: context filtering, least‐privileged retrieval, document-level ACL enforcement, vector store hardening, and secure token/secret handling.
Threat model AI systems (apps, agents, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/jailbreaks/data exfiltration) and build mitigations.
Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive-data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
Evaluate third‑party AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
Partner across Security, Data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
Lead/participate in AI red‑teaming: automated jailbreak/prompt‑injection tests, safety benchmarks, purple‑team exercises, and response playbooks for AI incidents.
Enable the org with concise guidelines, examples, and training on safe AI development and usage.

we are now looking for a tensorrt-llm software development engineer! our company is hiring software engineers for its tensorrt-llm team. academic and commercial groups around the world are using gpus to power a revolution in deep learning-powered ai, enabling breakthroughs in areas like llm, chatgpt and generative ai that have put DL at the iPhone moment for ai. join the team which is building the inferencing software which is foundational to product lines within our company and across the industry! the ability to work on a fast-paced delivery-focused team is required and excellent interpersonal skills are a must.
what you'll be doing:
craft and develop robust inference software that can be scaled to multiple platforms for functionality and performance
performance analysis, optimization, and tuning for large language models (llms)
conduct unit tests and performance tests for different stages of the inference pipeline.
closely follow academic developments in the field of artificial intelligence and feature update tensorrt-llm
write safe, scalable, modular, and high-quality ( C ++/ Python ) code for our core backend software for llm inference.
collaborate across the company to guide the direction of deep learning inference, working with software, research and product teams

we are in search of a top-tier ai agents solution architect to work closely with hardware architects, Verification engineers, gpu performance experts, and software developers to develop end-to-end agent flows that drive significant enhancements in simulation analysis, Kernel optimization, and Developer efficiency.
what you'll be doing:
develop innovative ai flows to improve hardware and software through collaboration with various engineering roles.
facilitate co-creation workshops to transform sme rules of thumb into specific assignments, resources, cues, and guidelines. define success measures, evaluation data, and feedback loops for agents to make a measurable difference in nvidia's hw simulation analysis and gpu- Kernel optimization workflows.
rapidly prototype and thoughtfully productize; integrate with internal services, utilize gpu capabilities, remove bottlenecks, and deliver fitting solutions.
set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements.
mentor and improve teams through insights in agent orchestration, prompting, rag, observability, crafting documentation and playbooks for teams.

you will work at the intersection of Machine Learning and software engineering - selecting the right models, feedback strategies, and evaluation frameworks to make ai-generated code reliable, high-quality, and trustworthy.
what you'll be doing:
design and build ai-powered development pipelines - from code generation and automated review to feedback loops and evaluation systems.
evaluate and select ml approaches for specific problems: when to use llm prompting vs. fine-tuning (qlora), classical ml (random forest, linear regression) vs. reinforcement learning, rag vs. structured extraction.
architect feedback and evaluation systems that measure and improve ai output quality over time.
review and refine ai solution architectures - evaluate design decisions, identify weaknesses, propose alternatives with reasoning.
lead proof-of-concept development to validate new ai/ml approaches for development tooling.
collaborate with the core team to define risk-based development levels and calibrate ai review depth per level.