לוח משרות דרושים הייטק AI , לחיפוש זה נמצאו 302 משרות

we are looking for a Senior AI Builder to take AI from a "promising demo" to real production systems that customers rely on - and that continue to work well over time.

Our R&D group is a team of 12 engineers and one architect, spanning backend to mobile, building the accounting platform businesses actually run on every day.



What you'll do

Build and ship LLM-powered AI capabilities to production- agentic flows, retrieval over our data, extraction from real-world documents, and more. Solutions need to be accurate, measurable, cost-efficient, and rollback-ready.
Build and lead the evaluation process - continuously measure the quality of models and solutions, and be able to answer clearly: is the new version actually better than last week's?
Own whatever it takes to get the solution into production- from AWS Lambda to Vue and PHP. You don't need to be an expert in every technology, but you should be comfortable getting into the code and solving problems wherever the work actually lives.

We're backed by tier-1 global VCs, led by second-time founders, and already deployed with organizations operating at serious scale. AI is not a feature here - it's the system.
We're hiring a Senior AI Engineer to design, fine-tune, and operate AI agents and large-scale models in production. This role exists because off-the-shelf models aren't enough for the problems we're solving.
If you enjoy pushing models until they break - and then fixing them - keep reading.
What you'll do:
Design and operate AI agents that reason, act, and collaborate with humans
Fine-tune and adapt large language models for:
Behavior analysis
Reasoning over long, messy timelines
High-precision enterprise workflows
Build agent orchestration systems (tool use, memory, planning, feedback loops)
Run large-scale inference and training pipelines in production
Work on model evaluation, drift detection, and continuous improvement
Optimize for latency, cost, and reliability at real enterprise scale
Partner closely with DevOps, security, and backend engineers - no research silos
Ship models that are auditable, explainable, and safe in sensitive environments

we are looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI - shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work.
This is a **cross-functional, company-wide role**. You won't be embedded in a single product team - instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization.
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
"our company's data management vision is the future of the market."- Forbes
we are the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, our company takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud.
Our success has been built through intense innovation, a customer-first mentality and a team of fearless company ronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our companys growth and at a pivotal point in computing history.
What You'll Do:
- Design, build, and operate LLM-powered applications, agents, and workflows end-to-end - from prototype to production.
- Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient.
- Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows.
- Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems.
- Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities.
- Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack.

LiveU is the global leader in live streaming and remote production, delivering high-quality, low-latency live broadcast solutions worldwide. We generate and process massive volumes of real-time device telemetry, operational data, and business metrics. We are looking for an experienced, hands-on Director of Data & AI join our Information Systems Department . In this role, you will define and drive our enterprise Data, Analytics, and AI roadmap. In this role, you will bridge strategic vision with technical execution- building a scalable cloud data platform, operationalizing production-grade AI, and driving company-wide AI adoption to create measurable business impact. Reporting to VP MIS Location : Kfar Saba (hybrid) Key Responsibilities : AI Enablement & Adoption: Lead company-wide AI literacy, change management, and adoption of GenAI tools (Copilot, ChatGPT Enterprise, custom agents) across R&D, Sales, Support, and Finance. Modern Data Platform: Architect and scale LiveU’s cloud data warehouse, unifying real-time device telemetry with enterprise systems and LivuU product (Salesforce, Priority ERP, AWS, and more). Applied AI & MLOps: Drive AI/ML initiatives from POC to production deployment (predictive models, RAG architectures, and AI agent workflows). Governance, Security & FinOps: Enforce data quality, security (GDPR, SOC 2), and AI guardrails while optimizing cloud compute and licensing costs. BI & Self-Service Analytics: Deliver executive-level dashboards and self-service BI capabilities for faster, data-driven decision-making. Leadership: Lead and mentor a team of data & AI engineers and analysts, fostering a culture of technical excellence and ownership.

We're building one of the most agentic, fast-moving AI products in the web search category - and we need a leader who can own it end to end. This is a cross-functional group leader role sitting at the intersection of AI product leadership and high-scale AI infrastructure: you'll lead the team building our agentic search product, and own the data infrastructure that indexes and caches the web at scale.

What Youll be Doing:
Set technical and product direction for an agentic web search AI system, from research and benchmarking through production and scale.
Bring deep, hands-on expertise in LLMs, agentic architectures, evaluation/benchmarking, and modern AI/LLMOps practices; make build-vs-buy and architecture calls with authority, not just strategy.
Lead and develop small group of two teams with top notch engineers, providing technical leadership, growing engineering managers, and driving execution across both product and infrastructure.
Drive the product to a category-winning position within an aggressive timeline.
Own the infrastructure supporting an API surface currently serving millions of calls/month, with a mandate to lead its growth to billions/month.
Bring proven, hands-on experience scaling high-throughput, high-availability infrastructure - not just AI-adjacent platform experience - including reliability, cost, and performance at that scale.
Own the data infrastructure needed to run the product, including large-scale data pipelines, storage, and operations.
Lead a worldwide web caching and indexing operation at high scale, ensuring freshness, coverage, and cost-efficiency of the index.

About the Role We are looking for a Head of RL Gym to own the end-to-end delivery, quality, and scaling of RL Gym programs for our strategic AI partners. You will work closely with frontier-model teams, Delivery, Product, Sales, Research, and Operations to turn complex customer and model-development needs into high-quality, scalable programs. What You’ll Own
* Own partner delivery from scoping through launch, execution, scaling, and iteration.
* Translate research and model needs into clear program requirements, workflows, and success metrics.
* Work closely with frontier-model teams to identify model gaps and design RL Gym programs that address them.
* Own quality standards and quality assurance, ensuring consistent, reliable outputs across programs.
* Build the processes, systems, and operating model required to scale programs efficiently without compromising quality.
* Partner with Sales on customer discovery, solution design, scoping, and expansion opportunities.
* Work closely with Product to translate partner needs and operational learnings into product requirements and roadmap priorities.
* Build strong feedback loops across customers, model teams, Sales, Product, and Operations.
* Own operational performance across quality, capacity, timelines, cost, throughput, and partner satisfaction.
* Build and lead the program management and operations function as the business scales.


About Alice:
Alice is 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, Alice 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. Alice is 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 seeking a highly experienced, AI-obsessed AI Senior Backend Engineer to join our core Engineering department. In this newly created, cross-functional role, you will be the driving force behind the companys internal AI transformation. You will act as the responsible for artificial intelligence, architecting, building, and deploying custom AI and automation systems from scratch to empower various departments and streamline operations.
Key Responsibilities
Architect, develop, and deploy tailored AI systems and applications from the ground up to solve organizational challenges.
Identify process bottlenecks across different teams and design robust backend automation solutions to optimize daily workflows.
Lead the hands-on integration of modern Generative AI models, APIs, and frameworks into the company's internal infrastructure.
Build scalable, high-performance backend microservices and APIs to support heavy data processing and AI workloads.
Act as the technical AI focal point, partnering closely with internal stakeholders and department heads to gather requirements and deliver high-impact technological solutions.
Collaborate with product, DevOps, and other teams to ensure that AI solutions are aligned with user needs and business goals.

We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across our platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales.

Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production.
Platform Integration & Intelligent Decision Systems: Develop MCPs to expose our capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?"
AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving.
R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support.
AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations.
End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production.
Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how we evolve from AI-enhanced internal tools to customer-facing AI products.

What you'll be doing

Set the AI roadmap for the company, and push AI initiatives across the organization.

Run the weekly AI review, where each function shows what it automated that week.

Enable the CEO directly, keeping him at the front line of AI technology, and drive tech stack improvements.

Work closely with R&D leadership to ensure cross-company collaboration.

Enabling the Sales, CX and Marketing teams to become AI-native.

Ramp every new hire on the ScaleOps AI stack within their first two weeks.

Audit every function for AI gaps and prioritize by revenue impact.

Measure adoption - hours saved, tasks automated, usage rate per skill.

We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team.
The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows.
You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations.

We are a well-funded, early-stage startup building our Founding Solutions Engineering team to help build and own our enterprise customer motion from the ground up. This role is perfect for a hands-on, technically deep builder who thrives in fast-moving environments, enjoys making things work in the real world, and partners closely with founders, Product, and R&D to deploy and scale complex, AI-driven enterprise solutions.
You will own the technical side of the post-sale customer journey, from deployment and integration through adoption, expansion, and ongoing success, while helping define how our delivery function evolves as we grow.

We are looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production.

You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure.

Responsibilities
Design, develop, and deploy LLM-based and Agentic Systems for production environments.
Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems.
Develop backend services and AI solutions using Python.
Work hands-on with agentic frameworks such as LangGraph, CrewAI, or similar/custom frameworks.
Deploy and operate AI systems in cloud environments.
Troubleshoot complex system issues and improve observability, reliability, and performance.
Collaborate with development, DevOps, security, and other technical teams.

We're looking for an exceptional AI Architect / Tech Lead (Hands-on) to help shape the future of our platform.
‍About the Role:
This is a highly technical, hands-on leadership role for someone who loves solving complex engineering challenges.
You'll lead the architecture and development of our AI initiatives while remaining deeply involved in coding, technical decision-making, and mentoring the engineering team.
If you're passionate about building AI-native products, designing scalable systems, and leveraging the latest AI technologies to accelerate development-you'll fit right in.
What You'll Do:
Design and lead the architecture of complex AI-powered features and services.
Build scalable Full Stack solutions using Node.js and React.
Develop AI-native products using modern LLM technologies.
Drive technical decisions, architecture, and engineering best practices.
Mentor developers through hands-on technical leadership.
Work closely with Product, Design, and Customer Success to deliver impactful solutions.
Explore and adopt the latest AI tools to improve both our product and development workflows.

we are looking for a AI Engineer (Mid-Senior).
What You'll Do:
- Build and harden AI Workers for real enterprise workflows - procurement, finance, HR, sales, risk, integration.
- Own the MCP connector framework - reusable tool servers that power every AI Worker.
- Design multi-step agentic flows with planning, reflection, retries, approvals, and clean failure modes.
- Ship evaluation suites that catch regressions before customers o.
- Instrument cost, latency, and reliability; drive them down relentlessly.
- Partner with Product and Solutions to ship features that survive contact with enterprise reality.

We are looking for an AI Engineer to build the backbone of our autonomous security platform.
our company builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives.
About the Role:
Youll design, build, and ship the AI systems behind Alex: production agents that reason over customer identity data, call real tools, and complete IAM tasks end to end. Starting from a cybersecurity need, youll frame the technical problem, choose an approach, and own the solution through production: architecture, implementation, evaluation, deployment, and iteration on real customer behavior.
Youll build on our companys shared agent infrastructure and extend it: new tools and integrations, workflow orchestration, context and memory management, evaluation harnesses, and the guardrails that keep an autonomous agent safe inside a customers environment.
This is a hands-on engineering role, not a research position. The goal is not to prove that an idea can work; it is to make it useful, reliable, and observable for customers in production.
What You'll Do:
Design, implement, and ship AI-powered features for complex cybersecurity workflows, from prototype to production.
Build the systems that make agents work in practice: tool integrations, planning and orchestration logic, context management, structured outputs, and recovery from failures.
Choose the right technical approach for each problem, combining models, deterministic logic, data, and conventional software where appropriate.
Define quality for each use case and build the evaluation pipelines that measure correctness, task completion, consistency, safety, latency, and cost, and wire them into CI and release.
Debug agent behavior in production: trace failures to their root cause in the prompt, tool, data, or architecture, and fix it.
Own the reliability, observability, and cost of the agent systems you build.
Collaborate with cybersecurity experts, product, and platform engineers throughout development.