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We're looking for a hands-on AI Tech lead to both build and guide. You'll architect and ship production GenAI systems while mentoring a team of engineers - keeping one hand on the keyboard and one eye on the roadmap. This isn't a seat at a whiteboard; it's a role for someone who can write a RAG pipeline in the morning and run a technical design review in the afternoon.
What you'll do:
Lead the design and delivery of end-to-end GenAI solutions, from prototyping to production - LLM-powered applications, agents, RAG systems, and fine-tuned models.
Stay hands-on: write production-quality code, review PRs, and set the technical bar for the team.
Define architecture patterns for prompt engineering, context management, retrieval pipelines, and model evaluation.
Mentor and grow a team of AI/ML engineers -run design reviews, pair-program, and provide technical feedback.
Partner with product, data, and platform teams to scope feasibility and drive AI initiatives from ideation to deployment.
Evaluate and introduce new models, tools, and frameworks (LangChain, LlamaIndex, vector DBs, etc.) as the space evolves.

We're looking for a AI Backend Engineer with a data science foundation to join our AI team and build production systems that integrate Generative AI capabilities. You'll design and implement end-to-end solutions APIs, databases, orchestration, and cloud infrastructure for clients across a wide range of sectors.
This role is ideal for someone who thinks in systems, enjoys working with GenAI technologies, and wants to grow into designing complex architectures. You'll work alongside senior engineers on real delivery projects from day one.
Key Responsibilities:
Design and build backend systems APIs, databases, authentication, and integrations
Implement multi-agent architectures and orchestration workflows combining LLMs with backend logic
Deploy and maintain systems on GCP, Azure, or AWS
Optimize AI system performance, cost, and reliability
Collaborate with client teams, DevOps, and stakeholders on project delivery
Contribute to technical discussions and solution design.

At our company, we build AI-powered vision systems that enhance safety and decision-making for some of the worlds largest vessels.
Our platform processes live video streams from multiple onboard cameras to provide real-time situational awareness, detecting and tracking marine objects, even in low visibility and highly congested environments. These systems directly support navigational decisions and help prevent collisions, reduce human error, and improve operational efficiency.
Our systems are already deployed across thousands of vessels and have processed hundreds of millions of nautical miles of real-world data, operating in unpredictable and safety-critical conditions.
This role sits at the intersection of AI and high-performance systems engineering, focused on solving real-world problems under strict constraints. You will work on systems where performance and reliability are critical and where improvements have a direct, measurable impact on real-world safety.
This is a senior, systems-focused role with end-to-end ownership over performance and reliability of production computer vision pipelines. You will define optimization strategies, identify bottlenecks across the system, and drive improvements under real-world constraints.
What youll do
Build and optimize real-time computer vision pipelines running on edge systems processing live maritime video streams (e.g, NVIDIA Jetson, Triton Inference Server)
Take models from research and turn them into production-ready, reliable components deployed on vessels
Profile and improve end-to-end system performance across: multi-camera video ingestion; preprocessing; inference; postprocessing
Identify and resolve bottlenecks across CPU, GPU, memory, and pipeline coordination
Make and justify tradeoffs between latency, accuracy, stability, and resource utilization
Design and implement robust data and inference pipelines (video -> model -> actionable output for crew)
Develop benchmarking and evaluation workflows to measure performance end-to-end and support release gating
Build and improve observability tools, including logging, monitoring, and debugging workflows for production systems
Define and maintain clear interfaces between research code and production systems
Work closely with research and backend teams to integrate new models into production systems
Continuously improve system efficiency and reliability under hardware and runtime constraints.

This is a role for someone who wants to build the org of the future, where agents and people work side by side, and is ready to own the program that gets a company there! Youre taking over the leadership of our AI Transformation: the internal AI work across every function. Youll own the program end-to-end.

What Youll Do?
Run the three pillars (Adoption, Infrastructure, Builds) and the foundation that ties them together. Adjust as we learn, and make it real on the ground.
Lead the change, not just the tooling - the hard part isnt building the agent, its getting people to change how they worked for years. Youll drive that change, build trust with VPs, and push where it matters.
Manage and grow the team - both direct reports and dotted line champions. Youll grow the team from there as the program scales.
Run the prioritization machine - choose whats the right effort, from vertical low hanging fruit and all the way to horizontal initiatives.
Make agents as employees real - every agent has a manager, a cost, a performance review, and a forward plan. Managers are measured and rewarded on how their agents perform.
Measure and report impact - hours saved, adoption, leverage and metrics you define and instrument. Report up. Adjust the program based on what the numbers say.
Stay hands-on - this isnt a role for someone who only writes plans. You build agents and workflows yourself when it makes sense, sit in proposal reviews with the PM, weigh in on architecture with the Engineer, and ship things when needed.

Location: Tel Aviv. Hybrid.

We're building the financial infrastructure that powers global innovation. With our cutting-edge suite of Embedded payments, cards, and lending solutions, we enable millions of businesses and consumers to transact seamlessly and securely. With 900+ employees worldwide and an R&D center of over 160 employees in Jerusalem - were reshaping how financial technology is developed and delivered..
The Role:
As AI capabilities accelerate across the bank, we need an engineer to design and enforce safe AI usage-protecting customer data, preserving model integrity, and meeting our regulatory obligations. You'll be the architect of guardrails, tooling, and policies that make AI both secure and useful for product and internal teams. This isn't about slowing things down; it's about building the trust layer that lets innovation move fast without breaking things.
Who You Are:
You're a security engineer who's excited about the AI wave-someone who sees LLMs and Agentic AI as fascinating puzzles to secure, not just threats to mitigate. You've spent 5+ years in Security Engineering, AppSec, or Cloud Security, and at least 1-2 of those years have been spent getting your hands dirty with LLMs, AI Agents and MCPs. You understand how agentic frameworks (LangGraph, CrewAI, AutoGen, and similar) orchestrate multi-step tool use-and where trust boundaries break down. You've assessed or secured AI-powered coding agents (Claude Code, GitHub Copilot, Cursor) and understand the unique risks of AI with filesystem, terminal, and API access in Developer environments. You're equally comfortable dissecting a prompt injection attack as you are writing a Terraform module or shipping a Python library. You know your way around AWS and/or Azure, modern app stacks ( Python /TypeScript, REST/gRPC, containers/Kubernetes), and can translate security requirements into Developer -friendly tooling-not just PDF policies that gather dust. You communicate clearly in English and Hebrew, thrive in regulated environments, and understand that security in financial services means mapping controls to frameworks like FFIEC, SOC 2, and PCI DSS-and actually having the evidence to prove it.
What Youll Actually Be Doing:
* Design enterprise AI guardrails across Azure and AWS (e.g., Azure AI Studio/Azure OpenAI, Amazon Bedrock/SageMaker): content filtering, PII redaction, prompt/response validation, and policy enforcement services.
* Assess and define secure usage patterns and data governance controls for agentic frameworks and coding agents: permission scoping, tool-call authorization, leastprivileged retrieval, session isolation, and MCP server governance.
* Threat model AI systems (apps, agents, MCPs, RAG, fine-tuning pipelines) using frameworks like STRIDE and the OWASP Top 10 for LLM Apps; define misuse scenarios (prompt injection/context poisoning/jailbreaks/ data exfiltration) and build mitigations.
* Build monitoring and telemetry: privacy-preserving prompt/response logging, sensitive- data detection, safety/eval dashboards, drift/abuse signals, and incident hooks into our SIEM.
* Integrate AI security into the SDLC: reusable libraries, pre-commit checks, CI/CD gates, policy-as-code, and secure-by-default reference architectures for product teams.
* Evaluate thirdparty AI vendors and internal apps: security reviews, data residency and retention requirements, SSO/SCIM integrations, DPA/TPRM inputs, and continuous control testing.
* Partner across Security, data, Privacy, and Engineering to map AI controls to FFIEC, SOC 2, and PCI DSS; document control evidence for audits.
* Lead/participate in AI redteaming: automated jailbreak/promptinjection tests, safety benchmarks, purpleteam exercises, and response playbooks for AI incidents.
* Enable the org with concise guidelines, examples, and training on safe AI development and usage.
 
Why Youll Love Working Here:
* Flexible hybrid.

The AI Forward Deployed Engineer (FDE) is responsible for driving the successful adoption of AI solutions across our Groups business units.

The role focuses on translating business needs into practical AI solutions and ensuring they are effectively embedded into real workflows, delivering measurable business impact.

FDEs work closely with business teams to identify high‑value opportunities, deploy and build customized AI solutions, and continuously improve outcomes. Success is measured by adoption, usage, tech quality and business value.


Key Responsibilities
Partner with business units and tech teams to identify and prioritize AI use cases.
Own AI initiatives end‑to‑end: from problem definition to deployment and impact measurement.
Deploy and adapt AI solutions to fit real operational workflows.
Drive user adoption through training, iteration, and feedback.
Support continuous improvement and scaling of successful solutions.

Join us to build cutting-edge systems, collaborate with world-class engineers, and shape how autonomous software is built in production.
We are looking for an AI Engineer to join the hunt.
Responsibilities:
Take part in the design and development of AI-driven features for our Dev-Native Observability Platform.
Collaborate with cross-functional teams to integrate AI solutions into existing systems.
Contribute to the product roadmap by identifying AI opportunities and providing insights as a potential end user
Stay updated with the latest AI trends and technologies to ensure our platform remains cutting-edge.

We are looking for a Head of AI to lead end-to-end internal AI adoption. This is a new role with a clear mandate: find where AI can make our teams faster and better at their jobs, then build and roll out the tools and workflows that make it happen. You will work with every department, from sales and marketing to finance, service, operations, R&D and HR, to find where AI can remove friction, speed up decisions, and unlock capacity. Then you'll own the full lifecycle: scoping the problem, designing the solution, building or configuring it, training the teams who'll use it, and supporting it after launch.

Responsibilities:

* Identify opportunities: meet teams across the company to understand their workflows, spot high-value AI use cases, and prioritize them by impact, effort, and ROI.
* Own the projects end-to-end: write requirements, propose solutions, set timelines and budgets, and make the business case (ROI) for each initiative. Align it with business priorities and present it to leadership.
* Build and deploy: create or implement the actual tools and workflows, whether that means configuring existing AI platforms, building custom applications, or integrating AI into tools teams already use.
* Train and support: get teams comfortable using what you've built. Stick around after launch to fix issues, gather feedback, and improve the solution over time.
* Prioritize and report: manage a portfolio of AI initiatives across the company and keep leadership informed on progress and impact.

We are a fast growing tech company in the automotive space with hubs across the US and Israel. We are disrupting the multi-trillion dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal driven, and, at our core, we believe every voice has value and can impact our bottom line. If you are a creative, solutions oriented individual who is ready to put your career in drive, we are the place for you! We are seeking a Prompt Engineer to join our product team and help take our AI-powered products to the next level. In this position you will be responsible for ensuring that our LLM workflows not only meet the highest standards of quality and reliability, but actively drive conversion and adoption across our products. You will design, validate, monitor, and optimize prompts, LLM workflows, and AI agents, with a sharp eye on business outcomes and conversion rates. The ideal candidate will possess excellent organizational and communication skills, a strong product and growth mindset, and the ability to collaborate effectively across many departments and teams. Most importantly, you will be genuinely passionate about modern AI tools and the practical adoption of LLMs in product development: you stay on top of what's new, experiment constantly, and bring fresh ideas to the team. This is a position based out of our Tel Aviv office or Jerusalem office, and will report to the LLM team lead.

What you will be responsible for:

* Design, prototype and iterate AI agents and LLM workflows from ideation to execution
* Drive conversion rate optimization (CRO) and product adoption for AI agents
* Monitor live systems (dashboards, A/B tests, validation pipelines), triage issues, and implement fixes for hallucinations and regressions
* Build and maintain LLM-as-judge frameworks to continuously evaluate quality at scale
*  QA and evaluate end user-facing AI output with a sharp eye on tone, messaging, and conversion effectiveness
* Collaborate with stakeholders across product, marketing, CX, and R&D teams

The top candidate will also have:

* Hands-on experience with using LLM pipelines in a product context
* Experience working with chatbots or conversational AI products
* Writing experience, such as copywriting, personal writing, UX writing background
*  JavaScript or basic scripting knowledge


Why you should join us:

* An awesome global team of forward-thinking, innovative go-getters
* Integrate with tech titans: work directly with APIs from Google, facebook, Microsoft, and more
* Be part of a rapidly scaling company poised for the future
* Learning and growth opportunities within a fast-paced tech startup environment
* Clear career advancement path for strong performers
* We are committed to setting each other up for success. As a member of our team, you will work in an environment that encourages growth, initiative taking, and continuous mutual feedback in order to reach your full potential.
* Cibus and lots of yummy treats:-)
Are you the one? apply here!

We are a fast growing tech company in the automotive space with hubs across the US and Israel. We are disrupting the multi-trillion dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal driven, and, at our core, we believe every voice has value and can impact our bottom line. If you are a creative, solutions oriented individual who is ready to put your career in drive, we are the place for you! We are seeking a Prompt Engineer to join our product team and help take our AI-powered products to the next level. In this position you will be responsible for ensuring that our LLM workflows not only meet the highest standards of quality and reliability, but actively drive conversion and adoption across our products. You will design, validate, monitor, and optimize prompts, LLM workflows, and AI agents, with a sharp eye on business outcomes and conversion rates. The ideal candidate will possess excellent organizational and communication skills, a strong product and growth mindset, and the ability to collaborate effectively across many departments and teams. Most importantly, you will be genuinely passionate about modern AI tools and the practical adoption of LLMs in product development: you stay on top of what's new, experiment constantly, and bring fresh ideas to the team. This is a position based out of our Tel Aviv office or Jerusalem office, and will report to the LLM team lead.

What you will be responsible for:

* Design, prototype and iterate AI agents and LLM workflows from ideation to execution
* Drive conversion rate optimization (CRO) and product adoption for AI agents
* Monitor live systems (dashboards, A/B tests, validation pipelines), triage issues, and implement fixes for hallucinations and regressions
* Build and maintain LLM-as-judge frameworks to continuously evaluate quality at scale
*  QA and evaluate end user-facing AI output with a sharp eye on tone, messaging, and conversion effectiveness
* Collaborate with stakeholders across product, marketing, CX, and R&D teams

The top candidate will also have:

* Hands-on experience with using LLM pipelines in a product context
* Experience working with chatbots or conversational AI products
* Writing experience, such as copywriting, personal writing, UX writing background
*  JavaScript or basic scripting knowledge


Why you should join us:

* An awesome global team of forward-thinking, innovative go-getters
* Integrate with tech titans: work directly with APIs from Google, facebook, Microsoft, and more
* Be part of a rapidly scaling company poised for the future
* Learning and growth opportunities within a fast-paced tech startup environment
* Clear career advancement path for strong performers
* We are committed to setting each other up for success. As a member of our team, you will work in an environment that encourages growth, initiative taking, and continuous mutual feedback in order to reach your full potential.
* Cibus and lots of yummy treats:-)
Are you the one? apply here!

Alice’s Innovation team builds adversarial RL environments that train the world’s most advanced AI models to be safer. Our customers are the leading frontier AI labs, who use these environments for post-training reinforcement learning and safety evaluation. This is the bleeding edge of AI safety technology: the environments you build will directly shape how next-generation models learn to resist adversarial attacks. We’re looking for an AI Software Engineer to own the RL Gym platform end-to-end: from architecting multi-site web environments that simulate real-world attack surfaces, to optimizing our in-house orchestration harness (AgenticVerse) for high-performance delivery into customer training pipelines. This is a builder role. You’ll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. You’ll interact directly with customer engineering teams to understand their infrastructure constraints and deliver environments that meet their scale and reliability requirements. Why this role This is one of the few roles in the industry where your code directly influences how the next generation of AI models are trained. You’ll be at the center of advancing AI safety, building systems that the world’s top labs depend on to make their models more robust. The work is technically deep, the problem space is genuinely novel, and the field is moving faster than any team can keep up with alone. There’s no playbook. You’ll write it. What you’ll do: Platform & performance
* Own and evolve AgenticVerse, our in-house orchestration harness that provisions and manages RL environments at scale. Focus on performance: low-latency provisioning, high concurrency, minimal overhead per environment instance
* Design and build isolated, reproducible web environments using Firecracker microVMs or Docker containers
* Architect multi-site scenarios (3-4 interconnected web applications per task) with rich interactions: drag-and-drop, file uploads, authentication flows, LLM-in-the-loop components
* Implement deterministic verifiers that evaluate agent behavior with zero ambiguity Customer delivery
* Work directly with engineering teams at leading AI labs to integrate RL Gym environments into their training and evaluation pipelines
* Translate customer specs into working environments, iterating rapidly on feedback
* Own the technical relationship: SLAs, API contracts, integration architecture
* Adapt environment delivery formats to cus tomer infrastructure (real-time API calls vs. offline batch, managed vs. raw artifacts)
* Build customer-facing UIs when needed (dashboards, environment configuration portals, monitoring interfaces) Rapid prototyping
* Take ambiguous problem descriptions and produce working prototypes within days, not weeks
* Validate new environment types, interaction patterns, and verifier approaches quickly
* Build internal tooling that accelerates scenario authoring and testing

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.

As our Salesforce & GenAI Builder you will be responsible for designing, developing, and implementing solutions on the Salesforce platform and other business application platforms, as well as architecting and deploying GenAI-powered solutions that improve and transform business processes. You will serve as a technical expert, ensuring scalability, reliability, and performance of our business application environment
Are you a highly skilled individual with a passion for Generative AI and a deep, hands-on understanding of Salesforce? Are you ready to take the next step in a dynamic career at the intersection of CRM implementation, development and cutting-edge technology?
our companys Information Systems department is expanding, and we have a unique opportunity for you to join our team as a Tech Specialist focused on Salesforce implementation and Generative AI innovation. We are seeking a skilled, passionate individual who possesses a strong technical background, deep Salesforce expertise, and hands-on knowledge of GenAI tools and architectures.

We are seeking a highly motivated and experienced LLM/ML Agentic AI Researcher to lead the technical development of our agentic AI interpretation framework. This hands-on role involves designing, building, and evaluating AI agents that interpret complex biological data.

You will be at the forefront of developing a sophisticated scientific reasoning system that leverages Large Language Models (LLMs) to provide structured, biologically-grounded explanations. Collaborating closely with immunologists, machine learning researchers, and technical leadership, you'll shape how we derive insights at a systems level, pushing the boundaries of AI in biology.

Location: Ramat Gan, Israel (Hybrid role)

What will you do?

Design, prototype, and build LLM-based agentic systems that reason over biological data, scientific literature, model outputs, and internal tools.
Develop agents capable of structured reasoning, hypothesis generation, explanation, planning, tool use, and iterative scientific analysis.
Build robust evaluation frameworks for agentic systems, including automated and human-in-the-loop evaluation pipelines.
Define and implement benchmarks, metrics, and test suites for measuring agent performance, including reasoning quality, biological grounding, factuality, robustness, reproducibility, and usefulness.
Work closely with AI researchers, computational biologists, immunologists, and product teams to translate scientific needs into measurable AI capabilities.
Create evaluation datasets and benchmark tasks that reflect real-world biological and therapeutic reasoning problems.
Analyze agent behavior, failure modes, hallucinations, tool-use errors, reasoning gaps, and grounding issues.
Contribute to the architecture of production-grade AI systems, including agent orchestration, retrieval, tool calling, memory, planning, and monitoring.
Stay up to date with the latest developments in LLMs, agentic AI, evaluation methodologies, and scientific AI systems.
Help turn research prototypes into reliable products used by internal teams and external partners.

Were seeking a Head of AI to lead research and engineering for multimodal foundation models and reasoning‑centric systems-from prototyping to reliable, secure, production deployment. The Head of AI will manage deep learning researchers, computational biologists, immunologists and engineers and partner closely with product leaders and company leadership to convert cutting‑edge methods into high‑impact, mission‑critical capabilities.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Team Leadership & Growth

Lead, mentor, and develop deep learning researchers, computational biologists, and machine learning engineers; set a high bar for scientific rigor, code quality, and delivery.
Establish clear ownership, role definitions, and growth paths; nurture a collaborative, low‑ego culture.
Technical Strategy & Delivery

Own the AI roadmap and architecture; guide model design, evaluation, and productionization (training, serving, observability, safety).
Build scalable pipelines for transformers, multimodal fusion, and reasoning/agent frameworks; champion reproducibility, CI/CD for models, and cost‑efficient GPU/TPU utilization.
Research Integration & Innovation

Stay current with the literature; run journal clubs and technical deep dives.
Evaluate, pilot, and integrate state‑of‑the‑art methods (advanced transformers, retrieval and tool‑use agents, causal/biological reasoning) into robust systems.
Cross‑Functional Collaboration

Translate biological and clinical questions into tractable AI projects with measurable impact.
Communicate complex trade‑offs to peers and executives; align plans, risks, and milestones across functions.
Mission & Impact

Prioritize initiatives that advance patient outcomes and create cumulative platform value.
Balance speed with scientific integrity, security, and compliance.

We are looking for an AI Engineer to play a central role in building, evaluating, and advancing AI models. You will own and evolve benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Own & Evolve Benchmarking - Design, build, and maintain benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.