As a Senior AI Engineer in the MSC IL AI Innovation team, you will lead the design, development, and productization of advanced AI solutions for our Specialized Clouds, with a strong focus on sovereign-first, secure, and responsible AI systems.

You will operate as a technical leader, owning end‑to‑end AI architecture and delivery, influencing platform direction, and mentoring engineers while working closely with architects, product managers, security, and operations teams. This role goes beyond implementation; you will shape how AI is built, governed, and scaled across sovereign and regulated cloud environments.


Responsibilities

Design and build AI agents that plan, use tools/APIs, manage state/memory, and reliably complete multi-step workflows.

Own AI features from design through production, including deployment, monitoring, and live‑site reliability, with an eval-first development lifecycle: define success criteria, build evaluation datasets and automated harnesses, and run human-in-the-loop reviews where needed.

Develop and maintain prompt, retrieval, and memory strategies (system prompts, few-shot examples, tool schemas, retrieval context) with proper versioning and evaluation coverage.

Debug AI behavior using prompt analysis, data inspection, and model/tool-call traces, and translate failure patterns into targeted improvements.

Establish and track AI quality metrics (e.g., accuracy, groundedness, relevance, hallucination rate) and integrate them into CI/CD release gates.

Optimize runtime performance and economics (token usage, inference cost, latency, caching, model selection/routing, batching) and implement monitoring and continuous improvement loops (online signals, drift detection, structured user feedback).

Partner with product, design, and domain stakeholders to define use cases, acceptance criteria, and rollout plans for AI features.

Live site responsibility.

CodeValue is looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production. You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure. Responsibilities
* Design, develop, and deploy LLM-based and Agentic Systems for production environments.
* Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems
* Develop backend services and AI solutions using Python
* Work hands-on with agentic frameworks such as LangGraph, CrewAI , or similar/custom frameworks.
* Deploy and operate AI systems in cloud environments
* Troubleshoot complex system issues and improve observability, reliability, and performance
* Collaborate with development, DevOps, security, and other technical teams.

We are looking for a hands-on Senior AI Engineer with real-world experience building and deploying LLM-based and Agentic Systems to production.

You will be responsible for taking AI solutions from concept to reliable, scalable production systems, working across AI, backend, cloud, and infrastructure.

Responsibilities
Design, develop, and deploy LLM-based and Agentic Systems for production environments.
Take AI/Agentic solutions from PoC and concept stages to stable, scalable, and reliable production systems.
Develop backend services and AI solutions using Python.
Work hands-on with agentic frameworks such as LangGraph, CrewAI, or similar/custom frameworks.
Deploy and operate AI systems in cloud environments.
Troubleshoot complex system issues and improve observability, reliability, and performance.
Collaborate with development, DevOps, security, and other technical teams.

Required AI Engineer
As an AI Engineer, you will:
Play a central role in advancing AI capabilities across the company and turning emerging AI technologies into practical, production-ready solutions
Research and evaluate new AI technologies, identify valuable use cases and develop solutions that improve internal workflows, existing products and enable new AI-powered capabilities
Lead AI solutions end to end, from research and proof of concept to design, development and production
Collaborate closely with development, product and business teams to integrate AI models, agents, data and reusable AI services into existing systems
Design and develop RAG, knowledge systems, AI agents and multi-agent workflows
Evaluate and benchmark AI models and solutions, balancing quality, accuracy, latency, throughput and cost
Find creative and practical solutions to complex technical and business challenges and help expand the companys internal AI ecosystem

As part of our team, you'll collaborate with software engineers, program managers, security researchers, and data science experts to develop solutions that protect, detect, and respond to evolving cybersecurity threats.  

Responsibilities
As a Software Engineer you will:

Contribute to business-critical initiatives in our Security.

Requiring deep technical skills and the ability to quickly adapt to new areas.

Improve the end-to-end lifecycle of services.

Analyze complex system behavior, and apply modern engineering practices to streamline deployments and reduce costs.

Your role involves working on high-end technologies and collaborating across disciplines to deliver impactful features.

Collaborate with multiple teams across us to deliver key customer solutions and support technology.

Leverage AI and AI-assisted engineering tools (such as GitHub Copilot) in your day-to-day work to accelerate development, automate routine tasks, and improve code quality - while exploring opportunities to integrate AI capabilities into the services you build.

we are looking for a Platform Enablement & AI Engineer.
The Platform Enablement & Automation team owns configuration management across products and services, defining how they operate for different customers, partners, and markets. This scope spans pricing and fee structures, eligibility and limit policies, onboarding, and the business rules and operational controls that govern product behavior across regions.
The team functions as the rapid-delivery layer between a business requirement and a fully productized solution. When a business unit requires a new capability, a pricing change, or a configuration deployed at short notice, the team delivers it at production quality without waiting for the full product and engineering build cycle. To operate at scale, the team builds and owns its internal platform, and is progressively evolving into an AI-native, automation-first function.
This is a hands-on, individual-contributor position focused on engineering delivery and technical ownership rather than people management. The successful candidate will serve as a core builder of the platform, working across the full technology stack, from user interface through backend services to data and deployment, and will provide the technical depth and redundancy that prevents the platform from depending on any single individual.
Working in close partnership with the business teams the platform serves, the successful candidate will translate their requirements directly into working software and help extend the platform outward as it grows to support strategic partners. The role also partners with the team's Director to shape the platform roadmap and deliver against it, in daily collaboration with R&D and Product in Glilot.

we are looking for a R&D Architect Director.
What youll do:
Drive new technologies and frameworks - extending capacity & effectiveness of teams, capacity & scalability of the product - for both server and client side
Be involved in all key technology and methodological aspects of development and testing
Take an active role and lead key product enhancements, per product-management and stakeholders requirements, and select the right development solutions to address the requirements in terms of functionality, reliability, testability, and scalability
Be involved in business needs and operational flows to come up with the right technology solutions
Mentor and lead R&D teams in design reviews, coding standards, and architectural designs
Drive AI adoption across R&D - both as a development accelerator (coding tools, agents, MCPs) and as a capability embedded in the product

we are looking for a AI Native Engineer (Node. js).
You will join a high-impact AI engineering team within R&D, owning problems end-to-end from understanding the business need, through architecture and implementation, to production monitoring. This is a new way of working at Payoneer: you'll work directly with business stakeholders, ship AI-driven capabilities at speed, and help define the methodology as we build it.
As a member of the AI Foundations organization, you will lead best practices, champion early adoption of new technologies, and influence the direction of our R&D guild - building and shipping cutting-edge agentic applications that deliver seamless experiences to our users.
Location
Hybrid - Herzliya, Israel
Full-time
What you'll do:
Own the full development loop understand the business problem, define the solution, architect it, build it, ship it, and monitor it in production
Use AI as your primary development tool, achieving in a day what used to take a team a week
Collaborate with your team and business stakeholders to define decision logic, risk thresholds, and success metrics
Design and build evaluation frameworks as part of every solution you don't ship what you can't measure
Own production readiness monitoring, alerting, and observability go in on day one
Contribute to shaping team practices, tooling, and engineering standards across the pod
Decompose business problems into agentic workflows, orchestrated flows, and reusable capabilities.

A Defense-Tech company developing advanced AI and real-world technology is looking for a Senior DevOps Engineer (Backend Oriented) to take ownership of its infrastructure and deployment environment. The role combines hands-on DevOps with real backend development, Docker, and production on-premises environments.



What Youll Do:

Design, build, and own production infrastructure across on-premises and cloud environments, including customer deployments, upgrades, remote management, and recovery.
Build and maintain Dockerized services and multi-container deployments using Docker Compose.
Own CI/CD, Infrastructure-as-Code, release processes, and deployment strategy from development through production.
Build observability across the stack, including monitoring, logging, alerting, and operational practices.
Manage GPU-based workloads and ensure AI workloads run reliably on real hardware.
Contribute to backend services and APIs, improving performance, data processing, database access, and real-time event handling.
Own networking, secrets management, security hardening, and infrastructure reliability.
Work closely with backend, ML, and product teams to improve scalability, deployment, and operational excellence.