לוח משרות דרושים הייטק AI , לחיפוש זה נמצאו 313 משרות

we care deeply about performance, clarity, and building tools that feel right. Were a small team of engineers who enjoy solving hard backend problems and working close to the data. If you're into Go, value clean architecture, and love building for other developers - this might be a great fit.

What Youll Do

Build high-performance backend systems in Go
Work on real-time data pipelines and large-scale telemetry infrastructure
Tackle tough challenges in distributed systems, scale, and performance
Collaborate with infrastructure, frontend, and product teams to ship features end to end

We are hiring Senior AI / Machine Learning Engineers to compose, build, and operate production AI systems across classical machine learning, computer vision, large language models, and agentic workflows. You will work across the full AI engineering lifecycle, from initial development and evaluation to deployment, observability, and ongoing improvement. This role suits engineers who can switch easily between system architecture and hands-on implementation. It is for those who understand what it takes to make AI systems reliable at production scale.

What youll be doing:

Lead the build and delivery of production AI systems across machine learning, computer vision, LLM, and agentic use cases.

Build AI applications and agents that use tools, complete multi-step workflows, maintain state, and operate safely in production.

Develop evaluation strategies, test suites, quality metrics, and production feedback loops for models and AI applications.

Build scalable architectures covering model serving, APIs, data flows, workflow orchestration, observability, security, and failure recovery.

Build durable, distributed workflows using platforms such as Temporal, Prefect, or comparable technologies.

Deploy, monitor, and continuously improve AI systems for quality, latency, efficiency, reliability, scalability, and cost.

Make informed technical decisions around model selection, inference architecture, context management, structured outputs, tool use, and infrastructure.

Establish effective development, deployment, and validation practices for services, models, workflows, and infrastructure And provide technical leadership through architecture reviews, build decisions, code reviews, mentoring, and engineering guidelines.

Own the intelligence layer - the AI research pipeline that classifies and risk-scores every tool we find. Discovery tells us what software an organization runs; the AI does the hard part: figuring out what each tool actually is, what it can do, how it handles data, and how risky it is. You'll own that research and enrichment system end to end - the LLM-backed agents, the prompts and context that drive them, the evals that keep them honest, and the cost and latency of running them at scale.

This is an engineering role, not a research one. You'll ship production TypeScript, and you'll be measured on the accuracy, cost, and reliability of the intelligence the product depends on.

What you'll work on

The multi-agent researcher system: LLM-backed agents that research each tool across topics like platform, data policy, AI models, and agentic capabilities, and return structured, evidence-backed classifications.

Evals and quality: design eval sets, measure classification accuracy and hallucination, and turn prompt changes into regression-tested, reviewable diffs instead of guesswork.

Grounding and trust: cite evidence, resolve contradictions between AI output and validated data, and drive down hallucination on the fields that matter.

Model routing and cost/latency: choose and route across providers, tune concurrency and caching, and keep the pipeline fast and affordable as volume grows.

Structured outputs, tool/function calling, and the schemas and validation that make model output safe to persist.

Deep observability into the pipeline - spans, traces, and metrics for every model call.

The same systems work as our senior role, aimed at someone earlier in their career who gets real work done in a hard codebase with agentic tools. Systems programming has a reputation for being locked behind ten years of experience. We don't fully buy that. Someone with solid fundamentals, real curiosity about how machines work, and deep control of agentic coding tools can contribute here much sooner - as long as they have the judgment to check what the tools hand back. That judgment matters more here than almost anywhere: the agent runs as root and SYSTEM, and the codebase forbids unwrap, panic, and unchecked indexing, so you can't ship code you don't actually understand.

What you'll work on

Real pieces of the sensor across macOS and Windows: inventory, telemetry, the policy enforcement path, installers, and the integrations that hook into AI coding tools and browser extensions.

Moving through unfamiliar OS APIs quickly with agentic tools, then checking the result against the docs, the tests, and a real machine.

Small tools and tests that make the codebase easier for everyone to work in.

Tech you'll work with

The work is low-level systems development in Rust, close to the operating system across Windows, macOS, and Linux - memory, processes, files, and the OS internals that expose them. Alongside that, you'll lean hard on agentic coding tools; deep fluency with at least one is central to how we work, not a bonus. Expect to range across the stack - OS internals, AI tooling internals, CI, and a fair amount of reverse engineering - and to learn the parts you don't know yet.

In Customer Care and Trust & Safety, real people are on the other side of every decision. You're the reason why our users feel safe using us, and you take that seriously. From Quality Assurance specialists to fraud analysts, those we're looking for are stakeholder-savvy and treat every case like it's the only one that matters. So if you're methodical when the details affect peoples livelihoods, we want to hear from you. Join our dynamic Customer Care team as a Chatbot Project Lead, taking the reins on our chatbot roadmap and stakeholder communication. This is a critical role stepping in to guide a talented team, ensuring seamless project delivery and strategic alignment as we enhance our AI-powered customer solutions.
What am I going to do?:

* Manage the end-to-end chatbot roadmap and sprint delivery, ensuring all project deadlines and key performance indicators are met with precision.
* Translate overarching company strategic goals into actionable chatbot experience improvements, effectively communicating updates and insights to diverse stakeholders.
* Mentor and provide hands-on guidance to team members, fostering their growth in areas like advanced prompting techniques on platforms such as Forethought.
* Leverage data analysis to deeply understand chatbot performance, driving continuous optimization and informing strategic decision-making.
* Facilitate key team meetings and foster a collaborative and inclusive team culture.
Equal opportunities:
We know that talent has no single face. We welcome talent from everywhere and everyone because it makes everything we build better. Need accommodations? Just ask. And if this role excites you but you don't tick every box, apply anyway. The best people rarely fit the mold exactly.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across our B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across our products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

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.

We are seeking a highly accomplished AI Researcher to be part of the development of next-generation Foundation Models and Generative AI systems. In this role, you will bridge the gap between cutting-edge academic research and production-grade AI infrastructure. You will build, design, and fine-tune large-scale architectures (including LLMs, Multimodal, and Tabular Foundation Models) while applying them to complex, real-world domains like agentic behavior, coding and decision making.
In your day-to-day, you will:
Conduct pioneering research in deep learning and generative AI, specializing in Foundation Models, NLP, alignment, and multimodal learning
Deal with the impact of the models on production traffic, cost quality and latency
Train and scale state-of-the-art architectures using techniques like Post-Training SFT, Knowledge Distillation, LoRA, and sparse/hybrid model architectures
Own the AI lifecycle-from algorithmic prototyping and synthetic data generation to deploying production-grade AI features in fast-paced or big-data environments
Drive research initiatives, author publications/patents, and collaborate with other research teams to integrate intelligent capabilities into core products.

Were looking for an AI Creative Gen- someone who lives and breathes visual creation and wants to redefine how video and stills are made. Think of this as the digital cinematographer of 2026. You dont just 'prompt'- you engineer multi-model workflows, integrate complex compositing techniques, and bridge disparate tools into a unified pipeline. You build, composite, and direct.
In your day-to-day, you will:
Own visual projects end-to-end - from receiving a storyboard to delivering high-end, cinematic video and stills using AI as your primary camera and studio
Direct the machine - apply your deep understanding of cinematography (lenses, lighting, camera angles, and composition) to guide AI models toward photorealistic perfection
Build & architect workflows - design and engineer hybrid production pipelines by integrating multiple models within WIVI. You will be responsible for orchestrating workflows that connect Midjourney, Image-gen models, and the latest video engines into a seamless output
Master the "non-AI" look - use VFX and compositing skills (After Effects/Premiere) to eliminate artifacts and ensure every frame feels intentional, grounded, and premium
Drive R&D through production - collaborate with the Motion Studio and Creative teams to solve high-complexity briefs. You dont innovate in a vacuum; you push the technical boundaries of AI within live projects, discovering new creative solutions and "impossible" workflows while executing at the highest level
Bridge the gap - combine AI-generated content with real-world photography or 3D renders to create seamless, high-fidelity brand stories.