לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 148 משרות

Were looking for a Founding AI Engineer to build and define the research function at our company from zero. This is a rare opportunity to work on some of the hardest unsolved problems in applied AI and agents, with massive ownership, visibility, and room to grow into leadership quickly.
What Youll Do
Lead the AI domain at our company: Take ownership of our agent architecture and help define its next phases, standards, and direction.
Solve hard, unsolved problems: Work on challenges in AI agents, reasoning over complex systems, and autonomous decision-making that dont yet have clear playbooks.
Build production AI: Design, implement, evaluate, and deploy AI systems used by real customers.
Be outward-facing: Publish technical blogs, benchmarks, and papers; represent our company in the AI and data community.
Move fast with autonomy: Own problems end-to-end with minimal guidance, working directly with founders.
Deliver real customer value end-to-end: take features from idea to production, see them used by customers, and iterate based on real-world impact.

As an AI Engineer at our company, you will own the intelligent decision-making pipelines that turn complex workspace telemetry into autonomous security actions. You will design, build, and deploy the autonomous reasoning workflows and advanced data classification systems that drive our company's preventive operating model. Your focus will be on creating resilient, production-grade AI systems capable of deep policy comprehension, real-time prevention at the point of adoption, and autonomous remediation of existing risks.
This is a ground-floor opportunity to shape the AI strategy of a fast-growing cybersecurity company alongside a lean, elite team of builders.
WHAT YOULL DO
End-to-End Ownership: Own our AI capabilities entirely from initial research, architectural design, and prototyping, through to production deployment, optimization, and continuous monitoring.
Design & Build Agentic Workflows: Architect multi-step AI agents capable of autonomously investigating workspace risks, interpreting complex enterprise policies, and taking precise remediation actions.
Integrate Multi-Faceted ML: Bring innovation and creative thinking to our core engine. Implement diverse ML models across our entire research and product pipeline-utilizing clustering, text extraction, document analysis, and tabular data classification.
Ship Production-Grade AI: Build high-throughput, resilient, and fault-tolerant production code. You will ensure our AI pipelines and agentic workflows are highly predictable, deeply observable, and built to scale under enterprise-grade loads.
Implement Guardrails & Evaluation: Build continuous evaluation frameworks to benchmark agent accuracy, mitigate hallucinations, and enforce strict data security/privacy guardrails.

We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our Automation Platform (DAP) team.
The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments.
You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure - running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns.
This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems - not model training or research prototypes.

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

End to end leadership of an AI product used by a wide range of users/systems
Responsibility for building the product roadmap
Gathering and prioritizing requirments, defining, specifications, consolidating needs, and building an operational concept
Ongoing collaboration with development and UX teams using agile methodology, with an understanding of technological implications
The position deals with the core of intelligence and the operational world, requiring interaction with numerous interfaces and familiarity with divers content areas
Monitoring development progress, execution measurement, implementation, and marketing
Keeping up with trends, technologies, and innovations in the AI field.

We are seeking a talented AI Specialist in DevOPS to lead the integration of artificial intelligence (AI) and machine learning (ML) technologies into our development, research, testing, and overall software systems. The ideal candidate will possess a deep understanding of DevOPS principles, coupled with hands- on experience in implementing AI models for code generation, automation, monitoring, and other critical functions.
עוד על התפקיד
In this role, you will design and establish robust infrastructure to support multiple development teams operating across diverse domains, technologies, and environments. We expect initiative, independent problem-solving, and innovative thinking to drive AI-driven solutions that enhance our software development lifecycle.

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.

Were looking for an Applied AI Engineer to join the Algorithmics team in a hands-on R&D role focused on building production AI systems for visual content creation. The role is less about training models from scratch and more about building intelligent systems on top of existing image, video, and language foundation models.
Youll work at the intersection of research, product, and engineering- building real-world AI capabilities used in production by creative teams.
Responsibilities:
Build AI workflows for visual content using image/video models, LLMs, and agentic systems.
Design orchestration and context-management layers (brand rules, assets, templates, user intent, constraints).
Prototype and validate new capabilities through data-driven experiments (metrics, evaluation sets, A/B testing, error analysis).
Take projects end-to-end from research to production deployment, monitoring, and iteration in cloud environments.
Work with AI-first development tools (e.g. Claude Code, Cursor, Codex) to accelerate development.

Required AI Algorithm Engineer - Vision Localization Group
Our vision Localization group is responsible for accurately localizing the vehicle on a high-definition 3D map with centimeter-level precision using surround camera systems to enable autonomous driving. Our work combines advanced geometric reasoning, scene understanding, and large-scale mapping to solve one of the core challenges of autonomous vehicles in complex real-world environments.
The role involves developing algorithmic and deep learning solutions that integrate mathematical optimization, computer vision, and 3D geometry. We work with modern neural network architectures including Transformers, GNNs, and CNNs to solve problems involving scene understanding, object association, and precise spatial reasoning in dynamic environments. The HD map contains rich geometric and semantic information that is critical for safe driving and cannot always be inferred reliably from images alone under all visibility conditions or viewpoints. In addition to achieving highly accurate localization, the team is also responsible for estimating map relevance and consistency with the current world state to ensure safe and reliable autonomous driving.
What will your job look like:
Develop state-of-the-art localization algorithms for autonomous driving using multi-camera surround vision systems.
Design and implement deep learning models based on Transformers, Graph Neural Networks, and Convolutional Neural Networks.
Solve challenging problems involving 3D geometry, scene understanding, object matching, and spatial reasoning.
Combine learning-based methods with classical optimization and geometric algorithms.
Own the entire lifecycle from prototyping to deployment.
Analyze real-world driving data and improve system robustness under diverse environmental and visibility conditions.
Drive innovative solutions for high-precision localization at production scale.

As our AI Team Lead, you will sit at the intersection of cutting-edge research and production engineering, guiding a high-performing team of Data Scientists and Engineers. This is a deeply hands-on leadership role where you will drive the end-to-end lifecycle-from initial research and PyTorch training to deploying sophisticated multi-modal AI (Text, Image, Audio, and Video) in high-throughput environments. Join us in building the future of responsible AI adoption and digital integrity.

Responsibilities
Manage and grow a high-performing team of AI researchers and engineers, fostering technical excellence.
Drive the design and training of multimodal models applications (Text, Image, Audio, Video) using PyTorch.
Own the AI roadmap from initial concept to scalable, high-throughput production.
Partner with Product, Backend, and Security teams to integrate AI solutions globally.
Stay at the forefront of GenAI/LLM research to continuously improve our detection engines.

abra is hiring for our Data & AI Division! We are looking for a Hands-on AI Developer to join our growing team and lead the development and implementation of cutting-edge AI solutions. What you'll do:
* Design, develop, and deploy AI solutions end-to-end
* Build intelligent AI Agents and AI-driven automations
* Develop RAG pipelines, semantic search capabilities, and information extraction processes
* Integrate AI solutions with enterprise systems through APIs and cloud services
* Work with documents, databases, structured and unstructured data sources
* Develop custom AI components using platforms such as Microsoft Foundry, OpenAI Platform, Claude Platform, Amazon Bedrock, Google Vertex AI Agent Builder, and Microsoft Copilot Studio
* Perform testing, debugging, monitoring, and optimization to ensure production-ready solutions

We are seeking a hands-on technical leader to architect and lead the development of production LLM-based applications. This role will lead a cross-functional team of software engineers and data scientists and will own architecture, delivery, evaluation, observability, and production readiness.



The ideal candidate is a proven software leader who has delivered complex production-grade systems and can align engineering, data science, product, and platform work into one cohesive execution model. The role requires strong software architecture, applied AI judgment, disciplined execution, and people leadership, with a focus on turning ambiguous product goals and exploratory AI work into reliable production software.



Responsibilities:

Lead a cross-functional team of engineers and data scientists developing LLM-based applications.
Translate product and business goals into technical roadmaps, milestones, and deliverable plans.
Own end-to-end delivery from architecture and experimentation through deployment, monitoring, evaluation, and continuous improvement.
Design LLM workflows using RAG, tool calling, structured outputs, agents, deterministic logic, and human-in-the-loop patterns where appropriate.
Establish evaluation-driven development practices for LLM features.
Define quality metrics, regression tests, golden datasets, production feedback loops, and observability standards.
Ensure systems meet production standards for scalability, performance, reliability, security, and maintainability.
Provide technical guidance, architectural oversight, mentorship, and career development for team members.
Manage priorities, scope, risks, and trade-offs across multiple streams of work.
Partner with product, design, DevOps, data engineering, security, and other technical leaders.
Drive continuous improvement in delivery quality, engineering practices, and team effectiveness.


We're looking for an AI Engineer to join our team. As an AI Engineer , youll be a key member of our founding team, designing, building, and deploying cutting-edge AI systems that leverage large language models (LLMs), unstructured data, and advanced ML techniques. Youll be instrumental in bringing AI from research to real-world production, delivering high-impact features that drive our security platform.

In this role, you'll have a unique opportunity to solve complex problems, work with large scale data and be part of the core team that shapes the future of AI in the company.


WHAT YOU WILL DO

Design and develop end-to-end AI solutions, from data ingestion and modeling to deployment and observability.
Build and fine-tune LLM-based applications to tackle complex cybersecurity challenges.
Own the full ML lifecycle - from ideation and experimentation to production readiness.
Collaborate with product, engineering, and security teams to turn AI research into user-facing features.
Work with large-scale unstructured data (e.g., logs, threat intel, alerts) to extract meaningful insights.
Evaluate and optimize AI system performance, scalability, and reliability.
Contribute to core architectural decisions related to AI and ML infrastructure.

We're looking for an AI Solutions Engineer to join our Transformation & Business Systems team. This role is built for someone fluent in AI-native building: you know how to vibe code a working tool end-to-end, you're hands-on with at least one automation platform, and you understand how LLMs, agents, and workflows actually fit together. You'll work directly with stakeholders across Finance, HR, Sales, Support, and IT to map manual processes and turn them into automated, AI-powered systems.

What Youll Be Doing:
Map manual, repetitive business processes end-to-end across the company - Finance, HR, Operations, Marketing, and the revenue funnel - and identify high-impact automation opportunities.
Own automation delivery from idea to production: translate requirements from non-technical stakeholders and design, build, test, and ship working solutions.
Build automated workflows using platforms like n8n, Zapier, Make, Tray.io, or Workato.
Design, build, and deploy AI agents that plug into real business workflows - embedding LLM APIs for use cases like ticket classification, document data extraction, and automated summarization, and applying RAG and memory patterns so they can reason over company knowledge.
Vibe code complete internal tools end-to-end using AI coding assistants - from rapid prototype (POC) validated with business users to something people actually use in production.
Connect internal systems (CRM, ERP, ticketing, Google Workspace/Microsoft 365) via APIs and webhooks, including AI-powered workflows for Marketing and Revenue teams - lead enrichment, campaign reporting automation, and pipeline data hygiene.
Monitor, maintain, and continuously improve existing automations - documenting processes and training internal process owners along the way.

We're hiring a Technical Enablement Specialist to own the rollout and adoption of AI and engineering, product and design enablement across our Product-Technology org. This is a sole-function, high-impact role - you will be the person who takes approved strategy and turns it into real execution, visible adoption, and measurable outcomes. This role reports directly to the Director of Product-Engineering Operations.
If you are a get-it-done person who loves working with people, knows how to drive change without heavy process, and is excited about where AI is taking software development - this role was written for you.
About the Role:
Lead AI adoption across Product-Technology - own the rollout of AI tools, agents, and AI-first practices; identify blockers and drive follow-up actions to move toward higher AI-generated code
Drive Agentic SDLC adoption - translate approved solutions and guidelines from Leadership into practical, consistent rollouts, including the POC framework and experimentation guidelines
Build scalable enablement programs - use AI to design and produce learning assets, workshops, and self-serve resources that keep pace with a fast-moving engineering org
Own knowledge management - maintain Confluence as the single source of truth for AI and engineering enablement; close content gaps with documentation, playbooks, and best practices
Foster a culture of continuous learning - coordinate the Engineering Forum, Engineering Guild, Product Guild, and AI community channels; identify opportunities for growth and keep the org current on AI tooling and industry trends
Partner with leadership and measure impact - collaborate with Product-Technology leadership to anticipate needs, define success metrics, and continuously improve programs based on data and feedback