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We're a team of Data Scientists, each owning a different model and domain of expertise. We're looking for a Senior AI Engineer to join us - someone who thinks fast, learns independently, and gets from problem to working solution quickly. You'll own your own models end-to-end while also raising the bar for how the whole team builds, evaluates, and ships ML.



What You'll Do

Design, build, and improve ML/AI models across domains - recommendation systems, image recognition, chatbots, and beyond.
Own the full ML lifecycle: data preprocessing, feature engineering, training, validation, and deployment to production.
Build evaluation pipelines that prove performance, scalability, and consistency - and that the rest of the team can reuse.
Apply generative AI and LLMs to improve existing workflows and identify new product opportunities.
Partner with Product, Engineering, and Analytics to keep modeling work tied to real business outcomes.
Translate complex model behavior and findings into insights stakeholders can act on.
Bring technical judgment to the team - share what you learn, and help keep practices consistent across different models and domains.

We are hiring someone to lead product level and internal team AI end-to-end: from protocol and architecture decisions to server-side implementation to the AI logic that decides when and how our tools are used, to internal processes that improve R&D and product development efficiency. This is a hands-on position with managerial aspects, not an advisory role. You will be building hands on in parallel to building the process and managing/guiding the team.

What You Will be Doing
Own the strategy and roadmap for AI strategy within R&D and AI agents specifically,
Lead the AI adoption effort technically within the product and across the organization as the company learns how to become more efficient with AI usage for R&D.
Design and build MCP servers that expose our APIs as well-described, reliably usable tools for AI clients.
Build the AI decision layer - the prompting, tool schemas, and agentic logic that let a model select the right API, pass the right parameters, and recover gracefully from errors.
Implement complete, production-grade features end to end: backend services, data models, APIs, and the AI integration on top, not prototypes.
Define how AI-accessible APIs are scoped, authenticated, and permissioned, so an agent can only ever do what it is authorized to do. Security is the product, this matters.
Build evaluation and observability for the AI layer: measure tool-selection accuracy, catch regressions, and trace agent behavior in production.
Set engineering standards and mentor others as the effort grows into a team.
Implement new features required by our cybersecurity product.

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

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation.

We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.

Were 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. Youll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. Youll 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. Youll be at the center of advancing AI safety, building systems that the worlds 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. Theres no playbook. Youll write it.
What youll 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.

We are looking for a Senior Backend Engineer specialized in Generative AI to design agent workflows, optimize interactions with models (OpenAI, AWS Bedrock), and ensure the reliability of non-deterministic systems in production.


What You'll Do
Agent Architecture: Design and implement complex agent orchestration logic using LangGraph. You will define state management, conditional routing, and error handling within the agent graph.
Tool Engineering: Build and optimize the tool layer (function calling) that allows LLMs to interact with internal financial APIs and databases accurately.
Performance Optimization:
-Reduce end-to-end latency through asynchronous processing and streaming (SSE).

-Implement semantic caching strategies to minimize API costs and response time.

-Optimize token usage without sacrificing answer quality.

Observability & Evaluation: Implement automated evaluation pipelines using LangSmith. You will be responsible for setting up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment.
Advanced RAG: Refine retrieval strategies. Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion to feed the most relevant context to the model.

Power the Future with us! At our company, we're a global leader in smart energy technology, with over 3,000 employees, offices in 34 countries, and millions of installations worldwide. Our innovative solutions include solar inverters, battery Storage, backup systems, EV charging, and AI-based energy management. We're committed to making clean, green energy the primary power source for homes, businesses, and beyond. With the growing demand for electricity, the need for smart, clean energy sources is constantly rising. our company offers amazing opportunities to develop your skills in a multidisciplinary environment, covering everything from research and development to production and customer supply. Work with talented colleagues, tackle exciting challenges, and help create a sustainable future in an industry that's always evolving and innovating. Join us and be part of a company that values creativity, agility, and impactful work. You'll own the product vision and roadmap for our ompany's data platform - the energy intelligence operating system spanning device integration, data infrastructure, AI/ML services, and third-party Developer enablement. This is a senior IC-to-lead role with direct influence on architecture decisions, partnership strategy, and organizational build-out. What You'll Do:
* Own the platform product roadmap across platform core layers
* Define and prioritize shared/core services with clear ownership, versioning, and SLAs
* Drive the semantic/ data layer strategy that enables internal products and external agents to consume energy intelligence
* Partner with engineering leadership on DevOps model, agentic dev lifecycle adoption, and platform reliability
* Work cross-functionally with business development to translate partner requirements into platform capabilities
Country:
Israel
City:
Herzliya

Next-gen Communications DSP & AI Software Development Engineer

Job Area

Engineering, DSP, Communications, 5G/6G, Algorithms, AI, Embedded Software

Location

Israel - Hod HaSharon

Responsibilities
Design and develop high-performance DSP software and optimized vector-processing kernels for wireless communications and AI workloads.
Implement low‑level DSP software with strong focus on performance, accuracy, and real‑time constraints.
Deliver high-quality, maintainable, and well-tested code while meeting project milestones.
Collaborate with team members and peer teams across multiple engineering disciplines.

Required AI Full-Stack Engineer
Our Continuous Security Validation enables companies to challenge, assess and optimize their cyber-security posture against the evolving cyberthreat landscape, simply and continuously.
With world-class clients we strive to bring the highest level of service to everything we do. Our team is made up of the very best people for the job and as we grow, were always on the lookout for people with the skills, experience, and personality that will let us both shine. With high scores on Gartner, G2 and Glassdoor, our clients and employees have let us know what they love about us.
What will you do:
Design, build, and maintain production-grade AI-powered applications and services.
Develop end-to-end full-stack solutions, including backend services, APIs, and modern React-based frontends.
Build scalable, secure, and highly available distributed systems.
Develop AI agents, copilots, autonomous workflows, and intelligent automation.
Build and deploy RAG (Retrieval-Augmented Generation) solutions and integrate LLMs into production.
Design AI orchestration workflows using frameworks such as LangChain, LangGraph, or similar.
Implement AI evaluation, tracing, and observability pipelines using Langfuse or equivalent tools.
Develop MCP (Model Context Protocol) integrations and AI tooling ecosystems.
Build and maintain cloud infrastructure, CI/CD pipelines, and Infrastructure-as-Code.
Drive engineering productivity through AI-assisted development and automation.
Collaborate closely with Product, Design, and Engineering teams to deliver customer value.
Research and evaluate emerging AI technologies and introduce innovative solutions.
Own features end-to-end-from architecture and development to deployment, monitoring, and continuous improvement.

we are looking for a AI Algorithm Tech Lead.
This is a role in core AI group, which specializes in developing cutting-edge AI solutions in healthcare, enhancing medical imaging and diagnostics. As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities:
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

We are looking for a professional to drive AI and business transformation initiatives, combining strategic thinking, execution discipline, and strong cross-functional stakeholder management.
This role will play a key part in shaping and driving AI-enabled transformation across the organization, working closely with business, product, AI, and IBT teams to translate strategic priorities into clear execution plans, adoption frameworks, and measurable business impact.
The role will be responsible for driving transformation execution governance, including initiative prioritization, business process understanding, dependency management, meeting outcomes, follow-up cadence, risk tracking, and cross-functional accountability across strategic initiatives.
Responsibilities:
Drive AI and business transformation initiatives from strategy into structured execution.
Work closely with business, product, AI, and IBT stakeholders to shape AI-driven capabilities and adoption processes.
Lead transformation execution governance, including planning, prioritization, follow-up, dependency management, and execution rhythm.
Translate business priorities into actionable plans, clear workstreams, and measurable outcomes.
Define KPIs, ROI models, and cost-related considerations to support decision-making and value realization.
Identify risks, gaps, dependencies, and blockers, and ensure timely escalation and resolution.
Build and implement transformation processes, governance structures, and execution frameworks.
Support senior stakeholders with clear communication, structured updates, and presentation materials.
Drive cross-functional alignment and accountability across multiple teams and initiatives.

we are looking for a AI Staff Software Engineer, ML Platform.
This is a Principal AI Software Engineer role at the heart of AI Engineering group-where algorithms, infrastructure, and products intersect. Youll lead the evolution and scaling of AI architecture, ensuring reliability, efficiency, and impact across global clinical workflows. The role combines technical depth with cross-functional influence, strengthening how our AI systems are built, integrated, and delivered to drive ongoing impact for patients and care teams.
Responsibilities:
Lead cross-domain engineering initiatives connecting AI algorithms (CV, NLP, and deep-learning systems), software, and data systems-from design to delivery.
Stay hands-on, contributing to AI-serving (training and inference), integration, and orchestration components while setting high technical standards.
Partner with Algo teams to connect algorithmic innovation with strong system design, ensuring smooth delivery across Product and Engineering.
Guide architectural evolution, ensuring efficiency, consistency, and maintainability across AI workflows.
Communicate direction and priorities clearly, aligning teams around technical goals.
Mentor engineers and promote technical excellence, sound design, and shared best practices.
Foster collaboration and shared ownership, helping maintain a culture that values clarity, curiosity, and technical excellence.
Uphold quality and reliability-including clean code, testing, and CI/CD discipline-while evaluating and adopting new tools that enhance performance and long-term scalability.