לוח משרות דרושים AI Engineer, לחיפוש זה נמצאו 168 משרות

We're looking for an AI Engineer to design and own the agentic infrastructure that spans the entire company

What You'll Do

Architect and ship agentic capabilities as production-grade product features - owning the full tradeoff space across reliability, observability, security, latency, deterministic behavior and cost.

Design and build AI agents that operate across Oak's identity graph, automating complex identity related workflows.

Evaluate and integrate emerging LLMs, agent frameworks, and agent infrastructure, making principled build-vs-integrate decisions grounded in production requirements.

Partner with R&D and product leadership to identify where agentic automation delivers the highest leverage across the product.

we are a leading creative technology company on a mission to empower creators and brands to bring their vision to life with video. Offering cutting-edge AI tools and models for image, video, and voiceover creation, alongside high-quality creative assets and powerful editing tools, our company enables creators to stay on trend and achieve their creative goals. Trusted by over 30 million creators worldwide and top brands including Google, Amazon, Microsoft, and Versace, our company provides a seamless, subscription-based platform with a global license, giving creators everything they need to produce professional video content efficiently. we are looking for an AI Enterprise Solution Expert to drive strategic AI sales across enterprise brands, media, and advertising. Working closely with sales leadership, this role will deliver hands-on AI expertise, custom-built solutions, proof of concepts, and Embedded creative services that enable brands to produce consistent, production-ready AI content at scale. Responsibilities
* Serve as the primary AI sales expert for a portfolio of existing and potential enterprise accounts, providing Embedded, high-touch engagement across pre and post sales, workshops, office hours, and ongoing advisory
* Guide clients through end-to-end AI content production, applying deep knowledge of pre-production, production, and post-production to ensure quality and consistency at scale
* Co-develop SOWs and build POCs with enterprise clients to move engagements from concept to execution
* Create high-impact AI product case studies and showcase projects
* Provide ongoing creative and Technical Support for strategic clients, helping transform initial demonstrations into successful long-term collaborations
* Translate product capabilities into compelling creative stories and business opportunities
* Support flagship initiatives and future showcase productions

As a Technical Policy researcher, you'll tackle some of the biggest and most complex questions of AI development and deployment. Your work outlining problems, solutions and principles for governments, frontier labs, and deployers will shape the emerging field of AI security.

Representative projects:

Threat modeling and fleshing out in what specific way could a strong cyber-capable model cause harm.

Taxonomies for dangerous AI capabilities or mitigations.

Policy proposals for models' refusal policy (which prompts models should refuse to follow).

Following up on publications and news on AI policy, AI risks and mitigations, and technical AI research.

Writing academic papers and blog posts detailing our research around evaluation theory or mitigation recommendations.

Publishing your research and/or delivering research to our customers.

We are looking for a Senior AI Engineer to design and build the intelligence layer .

You will own the agentic workflows, LLM integrations, and reasoning pipelines that allow our AI agents to autonomously analyze markets, make decisions, and drive eCom growth at scale.

What you'll do
Design & Build Agentic Workflows: Architect multi-agent pipelines - including planning, memory, tool use, and decision loops - that power autonomous media buying and growth operations.
Own LLM Integration: Select, prompt-engineer, fine-tune, and evaluate LLMs to produce reliable, high-quality outputs across diverse business tasks.
Build RAG Systems: Develop retrieval-augmented generation pipelines with vector search and context management to ground agent reasoning in real business data.
Drive Evaluation & Reliability: Define evals, build testing frameworks, and continuously improve agent output quality, consistency, and safety in production.
Collaborate Across the Stack: Work closely with backend engineers to integrate AI capabilities into core product APIs, ensuring low-latency, production-grade deployment.

We are looking for a Senior Data Engineer with a strong Backend Engineering background to architect the intelligent data foundation.

This is not a traditional ETL role. You will build the critical infrastructure that feeds our Agentic Growth Engine, enabling AI agents to perceive the market, make decisions, and drive growth. You will own the semantic layer, design the agentic data architecture (both data retrieval and training infrastructure), and build sophisticated extraction processes that allow our system to "read" the competitive landscape.

What you'll do
Architect the Agentic Data Infrastructure: Design and maintain the core data pipelines and storage systems (GCP/BigQuery/Postgres) that power our AI agents, ensuring high availability and low latency for decision-making.
Build the RAG & ML Backbone: manage the infrastructure for training data, vector search, and regression testing. You will ensure our agents have access to clean, context-aware data for RAG workflows.
Develop Agentic Extraction Processes: Build complex, resilient data extraction systems (crawlers/scrapers) to map competitive landscapes and product trends, feeding raw market data into our analysis engine.
Own the ELT & Semantic Layer: Manage the transformation of raw data into a consistent, business-ready semantic layer that serves as the "source of truth" for both analytics and AI models.
Run Predictive Models: Operationalize and deploy predictive models on top of our data, integrating them into the core product workflow.Define Data Standards: As a senior owner, you will establish the data engineering best practices, coding standards, and architectural patterns that the rest of the engineering team will follow.

As an AI Research Team Lead on Research group, you will mentor a talented team of researchers, set the strategic vision for research initiatives, and drive team-wide project goals. Youll partner closely with Product and Engineering leadership to turn open-ended data-security challenges into measurable experiments and shipped features. You will manage the critical balance between research exploration and product delivery, owning the end-to-end lifecycle-from problem framing and data strategy to evaluation, deployment, and ongoing monitoring-helping customers discover, protect, and govern their data at scale.



What Youll Do

Lead and mentor a team of AI researchers, fostering a culture of excellence and innovation while overseeing the end-to-end research lifecycle.
You will act as the technical and strategic lead, defining team priorities, roadmap, and data science methodologies.
Mentor and grow team members through technical guidance, career development, and peer reviews.
Collaborate with cross-functional leadership in Product and Engineering to align research efforts with core business objectives and customer needs.
Manage team performance, resource allocation, and timely project delivery within an agile environment.
Develop, evaluate, and maintain deep learning and NLP solutions to enhance Cyeras core capabilities in sensitive data classification.
Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems
Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification.
Join a full stack AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise.

we are looking for a Senior Full Stack Engineer - AI Team
Responsibilities



Direct contribution to the codebase as part of a product team.



Build and evolve customer-facing AI agents and agentic workflows powered by LLMs and AI models.



Work on product experiences that combine full-stack engineering, AI capabilities, security context, and customer value.



Collaborate closely with backend, QA, infrastructure, product, and design teams to understand, challenge, and translate end-user requirements into practical technical solutions.



Identify, document, and communicate technical improvements within your area of responsibility.



Participate in cross-team engineering initiatives as an individual contributor.



Help shape how AI agents are embedded into platform and used by customers to solve real security challenges.

Required xEngineer - AI Creation
Job Description
As an xEngineer at AI Creation, you'll take on some of the most exciting engineering challenges, shaping how AI becomes a core part of creating and editing stunning sites.
Take on engineering challenges to integrate AI as a first-class part of site creation and editing
Work on complex systems requiring deep technical understanding and collaboration with multiple engineering groups
Lead and own features end-to-end, from research and technical design to implementation and deployment
Collaborate closely with product managers, UX designers, and fellow engineers to deliver impactful solutions
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 and special requests are handled thoughtfully at the team level.

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.