לוח משרות דרושים AI Engineer משרה מלאה, לחיפוש זה נמצאו 184 משרות

we are looking for a Senior AI Engineer.
About the Role
In this role, you will:
Build Modular AI Capabilities: Design and implement self-contained "AI Skills" that connect to the CYE Platforms core data layers.
Ship End-to-End Autonomous Agents: Build agents that don't just "think," but act. You will deploy agents that handle the heavy lifting of the security lifecycle.
Bridge the Gap to Non-Technical Users: Create the abstractions that allow our customer success teams and client stakeholders to trigger or chain these AI workflows.
Own the AI Infrastructure & Evaluation: Maintain and contribute to the environment where these agents are born, ensuring they are grounded in truth.

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.

As a leading technology innovator, we push the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all.

As a company AI Software Engineer, you will develop and implement cutting-edge AI techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals.

In this position, you will be responsible for leading software development and implementation of the company AI Stack features within our AI Runtime (QAIRT) SDK, specifically Core software including Generative AI Inference Extensions. You will contribute to the efficient execution of advanced deep neural networks (DNNs), large language models (LLMs), and other modern AI architectures. You will also be responsible for supporting AI stack that optimizes runtime efficiency, latency and power consumption of AI applications running Machine Learning workloads on our low-power AI accelerators. The DSP core design work directly supports our NPU and GPU solutions, enabling optimized inference across diverse hardware platforms.

You will have the opportunity to demonstrate your passion for software design and development through your analytical, design, programming, and debugging skills.
Responsibilities
Develop real-time software for our AI DSPs to support the execution of the latest generative AI models on Snapdragon platforms

Develop and implement core components of our AI Stack runtime framework for inference on resource constrained AI systems, operating in low power, small memory footprint platforms

Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases

Debug complex issues, perform root cause analysis, and ensure high system reliability

Collaborate with cross-functional teams to deliver robust, scalable AI software solutions

Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team

Participate in design and code reviews

Working in global environment and collaborating inside the team and across other AI teams

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer to join our founding team. The focus of this role is to design, develop, and deploy autonomous AI agents that can automate and optimize complex enterprise workflows. You will work on building intelligent systems capable of decision-making, data extraction, document processing, and other tasks typically requiring human intervention. This is an opportunity to influence the architecture and strategy of AI-driven automation solutions for large-scale enterprise environments.

Your Impact
AI Agent Development

Design and develop autonomous AI agents using best of breed large language models to automate tasks such as document processing, data extraction, and workflow management.

Implement reinforcement learning techniques to enhance decision-making capabilities of AI agents.

AI Integration

Build and integrate APIs that connect AI agents with external systems and enterprise software (ERP, CRM).

Use frameworks like TensorFlow, PyTorch, or Hugging Face to deploy and optimize AI models for real-time processing.

Data Processing and Pipelines

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data efficiently.

Optimize data handling to improve speed and accuracy of AI agents.

Security and Compliance

Implement authentication and authorization mechanisms to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g., GDPR, HIPAA) and adopt best practices for secure data handling.

Cloud Infrastructure and Scalability

Deploy AI agents on cloud platforms (AWS, GCP, or Azure) ensuring scalability and reliability.

Leverage containerization (Docker, Kubernetes) for efficient deployment and management.

Testing and Optimization

Develop and execute unit, integration, and performance tests for AI-driven systems.

Continuously monitor and optimize system performance for speed, accuracy, and cost-efficiency.

Collaboration

Work closely with AI researchers, front end engineers, and product teams to align AI agent capabilities with business requirements.

Participate in code reviews, design discussions, and architecture planning to drive innovation.

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.

Your Impact
AI Agent Development

Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows.

Workflow Automation

Build machine learning pipelines to automate content-heavy processes for enterprise businesses.

Model Optimization

Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy.

Collaboration

Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations.

Evaluation & Testing

Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios.

We are a well-funded, early-stage startup looking for a Frontend / Fullstack Engineer to join our founding team. In this role, you will help build cutting-edge web applications and platforms that bring autonomous AI agents to life, automating complex enterprise workflows. You will play a critical role in shaping intuitive, responsive UIs and robust backend APIs that connect AI-driven agents to real-world enterprise systems (ERP, CRM, and more).

This is an opportunity to influence the architecture, design, and user experience of next-generation AI-powered automation solutions for large-scale enterprise environments.

Your Impact
Product & Frontend Development

Design and develop modern, intuitive, and responsive frontend interfaces that allow users to interact seamlessly with AI agents and automated workflows.

Create user dashboards, workflow builders, and visualization tools to monitor AI-driven automation in real time.

Collaborate with design and product teams to bring complex AI capabilities into simple and usable UI experiences.

API and Fullstack Engineering

Develop robust backend APIs that connect AI agents to enterprise data sources and external systems (ERP, CRM, document management systems).

Implement REST and GraphQL APIs to expose AI agent functionalities to the frontend.

Handle real-time communication, event streams, and notifications to keep users informed of workflow progress.

AI Integration & Collaboration

Collaborate closely with AI/ML engineers to integrate AI agent outputs into the product, including document processing, data extraction, and decision-making workflows.

Manage and present AI agent-generated data in user-friendly formats and visualizations.

Team Collaboration & Culture

Work closely with AI engineers, product designers, and enterprise customers to align AI capabilities with real business needs.

Participate in code reviews, architecture discussions, and feature planning.

Help shape the companys engineering culture and best practices as part of the founding team.

We are a well-funded, early-stage startup looking for a talented and motivated Backend Engineer specializing in infrastructure to join our founding team. The focus of this role is to build and scale the infrastructure that powers autonomous AI agents automating complex enterprise workflows. You will own the systems, pipelines, and platforms that let our AI agents run reliably, securely, and at scale in production.

Your Impact
Infrastructure & Platform

Design, build, and own the core infrastructure powering our AI agent platform, from data pipelines to production deployment systems.

Build and scale the backend systems that support high-throughput document processing and data extraction workloads.

Cloud Infrastructure and Scalability

Architect and deploy infrastructure on cloud platforms (AWS, GCP, or Azure) with a focus on scalability, reliability, and cost efficiency.

Own containerization and orchestration (Docker, Kubernetes) for all production workloads.

Build and maintain CI/CD pipelines and DevOps practices that let the team ship fast without breaking things.

Data Infrastructure

Design and manage data pipelines to process and analyze large volumes of documents and unstructured data at scale.

Build the infrastructure layer connecting AI agents to databases, vector stores, and enterprise systems (ERP, CRM).

API & Systems Integration

Build and maintain robust, well-documented APIs connecting AI agents with external systems and enterprise software.

Design for reliability: retries, observability, and graceful degradation across distributed systems.

Security and Compliance

Implement authentication and authorization mechanisms (OAuth2, JWT) to secure AI-driven systems.

Ensure compliance with data privacy standards (e.g. GDPR, HIPAA) and drive best practices for secure data handling across the infrastructure.

Monitoring and Optimization

Build observability and monitoring systems to track infrastructure health, performance, and cost.

Continuously optimize system performance for speed, reliability, and cost-efficiency at scale.

Collaboration

Work closely with AI/ML engineers, product, and the founding team to make sure infrastructure decisions support fast iteration and production-grade reliability.

Participate in code reviews, design discussions, and architecture planning to drive infrastructure strategy.

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.

Your Impact
Customer Onboarding & Process Analysis

Engage with customers post-close to understand workflows, operational processes, and deployment requirements.

Translate findings into clear implementation plans for AI-powered solutions.

Data, AI Models & Workflow Development

Partner with customers to assess data readiness and gather inputs for AI workflows.

Configure and integrate AI components into tailored, AI-driven workflows.

Collaborate with R&D to close data gaps and extend product capabilities when needed.

Deployment & Proof of Value

Own end-to-end solution deployment and ensure models meet performance and business value expectations.

Define success metrics and drive adoption post-launch.

Integration, Security & Rollout

Lead integrations with enterprise systems (e.g., Finance, ERP, email platforms), ensuring scalability and security.

Guide customers through security, compliance, and IT approval processes.

Plan and execute rollout to drive smooth implementation and adoption.

We are looking for a Generative AI Engineer to lead our AI efforts end-to-end - from infrastructure and production systems to internal adoption and cross-team enablement.
You will play a significant role in building the world's first Consumer Therapy AI Product (someone said RAG? But we mean a real one that works in production...).
This is a critical role in a high-growth, fast-paced B2C startup, requiring a leader who can advocate for Engineering requirements, tech-debt and best practices while promoting a product-mindset and putting our customers front and center.
About You:
You are a great human being and youre all into teamwork. you care about how people will feel inside the organization and set high standard for culture, professionalism and maturity.
A Doer, hands-on, biased for action and not taking an advisory role. Know how to translate challenges into actions. Able to work both individually and manage multiple priorities while driving others around you for action.
You're a fast learner, jack of all trades, feel comfortable in a fast paced, ever-changing environment. You can break down complex problems into steps and plot clearly how to get from A to Z while having the ability to zoom out and see the bigger picture.
You are an experienced hands on engineer, with proven experience with Developing LLM based products, with a real passion to AI and LLM, eager to learn about very new model and technology in this domain, and have a real understanding of the AI ecosystem

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 hiring a GenAI Engineer to join a team building and delivering real-world generative AI solutions - systems that move beyond prototypes and into production, where real users rely on them every day.
You'll take complex problems from the first customer conversation through to a working system running in their environment. You'll build GenAI solutions that are deployed, used, and relied upon - not just demos or experiments.
The problems are unusual, and the constraints are real: on-premise and air-gapped deployments, strict data handling requirements, and complex customer environments. A meaningful part of your work will happen on-site with the people who use the systems you build.
What you'll do:
Build end-to-end GenAI systems: RAG pipelines, agentic workflows, document understanding, and extraction from messy real-world data.
Own the full lifecycle - from data pipelines and model/prompt design to evaluation, deployment, monitoring, and the critical work of making systems reliable and production-ready.
Define what success looks like for each use case, measure performance, and stand behind the results.
Work directly with customers on-site, translating their needs into practical technical solutions.

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 the 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 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 evolves from AI-enhanced internal tools to customer-facing AI products.

We're looking for a Head of Research to establish and lead research group - a strategic and hands-on leadership role for someone who thrives at the intersection of AI, infrastructure, and systems innovation. You'll identify high-impact research directions, validate cutting-edge technologies, and drive new approaches that translate into long-term competitive advantage . This is not an academic position, but an opportunity to build a research function that directly shapes product and technology.

Define and lead the company's research agenda in AI, infrastructure, and distributed systems
Explore and evaluate new algorithms, architectures, and approaches relevant to large-scale AI workloads and cloud cost efficiency
Collaborate with product and engineering to translate research into real-world impact
Build and manage a small, high-caliber research team
Publish findings, represent in the AI/infrastructure research community, and establish partnerships with academia and industry
Act as a thought leader driving innovation across the company

We're looking for a Senior Applied Researcher and Team Lead to help shape how our conversational agents are designed, evaluated, and shipped reliably at production scale.



Key Responsibilities

Partner directly with the Applied Research Team Lead to define and evolve team process, technical standards, and the quality bar for agent behavior.
Take real user experience and data through the full arc, from concept to a reliable agent design to a shipped, production-grade product.
Own or share ownership of the standing function of assessing AI tools, models, and providers for reliability and fit.
Raise the technical bar across a team spanning research-leaning grad students to engineers newer to AI, and turn personal expertise into shared tooling and standards the whole team can use.
Operate pragmatically inside current infrastructure constraints while flagging where structural fixes are needed.