לוח משרות דרושים AI Engineer בתל אביב יפו

XM Cyber is a global leader in hybrid cloud security. XM Cyber brings a new approach that uses the attacker’s perspective to find and remediate critical attack paths across on-premises and multi-cloud networks. The XM Cyber platform enables companies to rapidly prioritize and respond to cyber risks affecting their business-sensitive systems. We are seeking a highly skilled and motivated Backend Enginee r with a Generative AI orientation to join our Infra team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities across our product line. This platform will handle cross-team concerns, such as prompt management, model access, data filtering, logging, and monitoring, centrally, so individual teams can focus on their own business-specific logic. As a Backend Engineer with a Generative AI orientation, you will be instrumental in designing, developing, and implementing the core services of this foundational AI Platform. You will build components that enable our development teams to quickly innovate with AI while adhering to high standards for quality, cost-effectiveness, and compliance. Responsibilities:
* Develop and maintain a centralized microservice that handles all AI model interactions.
* Build shared services and libraries to maximize development speed and cost-efficiency for AI based features/systems across the company
* Setting the tone in the fields of automatic testing strategies and CI/CD for AI components, prompt management, and more.
* Define and enforce best practices for model governance, security, and compliance.

We are seeking a highly skilled and motivated Backend Engineer with a Generative AI orientation to join our Infra team.

We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities across our product line.

This platform will handle cross-team concerns, such as prompt management, model access, data filtering, logging, and monitoring, centrally, so individual teams can focus on their own business-specific logic.

As a Backend Engineer with a Generative AI orientation, you will be instrumental in designing, developing, and implementing the core services of this foundational AI Platform. You will build components that enable our development teams to quickly innovate with AI while adhering to high standards for quality, cost-effectiveness, and compliance.

Responsibilities:

Develop and maintain a centralized microservice that handles all AI model interactions.
Build shared services and libraries to maximize development speed and cost-efficiency for AI based features/systems across the company
Setting the tone in the fields of automatic testing strategies and CI/CD for AI components, prompt management, and more.
Define and enforce best practices for model governance, security, and compliance.

As a Senior LLM Applications Developer, youll design and integrate Large Language Models (LLMs), agentic AI, and AI agents into production at scale. Youll architect backend systems, optimize prompts, and lead technical decisions that define how AI powers our caregiving platform. Beyond coding, youll mentor the team and pioneer new agent-driven AI capabilities that drive our mission forward.



What Youll Do

Design and develop backend services for AI-driven applications
Architect and optimize prompts for LLMs in production
Integrate AI/LLM models into scalable, secure, cloud-based systems
Collaborate with AI, Product, and Data teams to deliver impactful features
Mentor developers and set best practices in backend engineering
Explore new AI models and tools, leading adoption into production

As an LLM Applications Developer, youll design and implement backend applications that integrate LLMs, agentic AI, and third-party AI services into production. Youll engineer prompts, build scalable systems and AI agents, and collaborate closely with R&D and Product teams to deliver high-impact AI features.



Key Responsibilities

Develop backend services that integrate LLMs and AI tools into production
Engineer and optimize prompts for performance and accuracy
Build scalable, reliable cloud-based solutions (AWS)
Collaborate with R&D and Product on technical design and delivery
Research and experiment with new AI models and tools

Required Software Engineer - Al Platform
About Us
We help modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, weve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over ~4500 midsize and multinational companies and over 1 Milion users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
What this role is really about
Were building our internal AI Platform as a foundation that enables safe, scalable, and cost‑effective AI across the company. Our mission is to support internal business units in becoming more productive and driving business growth. As a Software Engineer on Business Innovation (Internal), youll develop high‑leverage platform capabilities used by Product, Customer Success, Sales, Operations, Data, and IT. Youll work across the entire stack, from APIs and services to data and UI. transforming business requi
Build core AI platform services - Design and implement agent orchestration, prompt management, RAG, Connectors, and evaluation pipelines that power AI experiences across the company.
Develop complex agentic workflows - Develop a multi-step workflow that coordinates tools and services with proper observability, guardrails, and cost controls (using OpenAI Agent SDK, LangGraph, or a similar framework).
Build LLM evaluation and optimization systems -Develop evaluation harnesses, offline/online experiments, prompt-testing frameworks, and dashboards to balance quality, latency, and spend across all AI services.
Ship the internal AI portal - Build user-facing products that democratize AI access: prompt directories, agent designers, templates, approval workflows, and more.
Ensure security and compliance - Develop RBAC, data classification, PII redaction, audit logging, and policy enforcement.
Create robust integrations - Connect the platform with Salesforce, NetSuite, Slack, Snowflake, HRIS, and other critical business systems.
Establish operational excellence - Implement CI/CD, testing strategies, monitoring/tracing, and SLOs for high-reliability services.
Enable developers - build SDKs, CLIs, and templates that help teams create safe, scalable AI workflows. Lead technical discussions and write design documentation.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.

In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.

You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.

If you enjoy working at the intersection of AI and engineering bringing models to life in production, optimizing for performance, and building reliable systems this role is for you!

Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models

We are looking for a forward-thinking Data Scientist with a passion for Generative AI (GenAI) and emerging AI technologies. This role is ideal for those who thrive in rapid prototyping, proof-of-concept (PoC) development, and iterative experimentation. You will work across multiple projects, transforming innovative ideas into practical AI solutions while engaging with clients for feedback and improvement.

Responsibilities
Generative AI Innovation & Research: Design PoCs with LLMs, RAG, RL, and agent-based AI. Apply emerging AI methods to real-world business needs.
Prototyping & Implementation: Translate research into scalable prototypes and production solutions. Ensure models are efficient, adaptable, and enterprise-ready. Lead integration, A/B testing, and phased rollouts.
AI Engineering & Deployment: Architect scalable GenAI solutions for banking. Own the full lifecycle: deployment, monitoring, incident response. Build dashboards, detect model drift, and integrate feedback loops.

we are looking for an AI Platform Engineer to revolutionize engineering productivity and drive AI-powered innovation across the organization. This role is part of our Platform Engineering initiative, focused on enabling engineers and product teams with cutting-edge AI tools, automation, and scalable AI platforms.
If youre an innovator at heart, passionate about leveraging AI to solve complex problems, and thrive in an environment where experimentation and entrepreneurship are encouragedthis role is for you.
Responsibilities:
 Develop and integrate AI-powered solutions to enhance engineering productivity, automate workflows, and improve developer efficiency.
Evaluate and implement state-of-the-art AI platforms (ChatGPT, Claude, Gemini, custom models) to solve engineering and operational challenges.
Design and maintain AI-driven internal platforms such as knowledge management systems, AI-enhanced coding assistants, intelligent automation tools, and AI-powered chatbots.
Work alongside engineering, DevOps, and product teams to embed AI into everyday development workflows.
Lead Proof-of-Concept (PoC) projects, experimenting with LLMs, generative AI, and automation frameworks to create tangible business impact.
Stay ahead of emerging AI trends, researching and implementing cutting-edge AI models and tools.
Build scalable AI infrastructure that integrates with cloud environments (AWS, GCP, Azure) and engineering toolchains.
Promote a culture of innovation, empowering teams to embrace AI-driven solutions and fostering AI adoption across the organization.

We are looking for a talented and motivated Software Engineer to join our newly formed team developing orchestration tools and platforms for AI datacenters.
The main goal of this team is to create customer-focused orchestration solutions that simplify the deployment, management, and optimization of large-scale AI workloads across a full datacenter stack including switches, hosts, smart NICs, GPUs, ROCm, and RCCL.
You will work on the design and development of orchestration systems that bridge compute, networking, and AI acceleration domains, primarily using Python and modern full-stack technologies.
Key Responsibilities
* Design and develop software components for orchestration platforms managing AI datacenter infrastructure.
* Implement control and coordination mechanisms for compute, network, and AI acceleration resources.
* Develop backend services, APIs, and UI components using Python and modern full-stack frameworks.
* Collaborate with cross-functional teams including networking, GPU, and system software to integrate orchestration capabilities across multiple layers.
* Participate in architecture discussions, code reviews, and continuous integration processes.
* Contribute to testing, validation, and performance improvements of orchestration systems.
* Engage with product and customer teams to translate operational needs into effective software solutions.

We are seeking a highly skilled and motivated Team Leader to build and lead a new team dedicated to developing orchestration tools and software solutions for AI datacenters.
The main goal of this team is to design and deliver customer-focused orchestration platforms that simplify the deployment, management, and monitoring of large-scale AI workloads.
This role combines technical leadership with hands-on development, covering the entire AI datacenter ecosystem including switches, hosts, smart NICs, GPUs, ROCm, and RCCL. The team will primarily develop in Python, complemented by modern full-stack technologies for user interfaces and control systems.
Key Responsibilities:
Lead and mentor a team of engineers building orchestration tools that manage complex AI datacenter infrastructures.
Define the teams vision, roadmap, and architecture for orchestration solutions that enhance customer experience and operational efficiency.
Design and implement distributed control and orchestration systems using Python and full-stack frameworks.
Collaborate with networking, compute, and AI acceleration teams to integrate orchestration capabilities across all datacenter components (switches, NICs, GPUs, and software stacks).
Work closely with product, QA, and DevOps teams to identify customer requirements and translate them into scalable, production-grade orchestration platforms.
Ensure software reliability, scalability, and maintainability through strong design principles, testing, and CI/CD practices.
Foster a culture of innovation, technical excellence, and cross-functional collaboration.

We're looking for an Autonomous Product Manager to supercharge efficiency across internal teams. If you love turning messy, multi-team processes into elegant, automated workflows with GenAI and agentic systems and you enjoy shipping pragmatic solutions that measurably reduce cycle time and operational cost this role is perfect for you.

In this role you'll:
Own cross-company automation initiatives end-to-end from discovery and scoping through MVP, rollout, and continuous improvement

Map complex processes and identify leverage points for automation and assisted workflows

Leverage GenAI and automation platforms (like n8n) to build and deploy agent-based products, taking them from concept to full production

Operate in a microsquad leveraging existing platforms and your hands-on skills to deliver products from early POC to working solutions in production

Instrument everything define baselines, ship dashboards, and track impact (hours saved, cycle time, accuracy rates, SLA adherence, auditability)

Shepherd change management with stakeholders through crisp docs, training sessions, feedback loops, and landing new ways of working

Partner deeply with engineering, data, and design teams to prioritize the highest-ROI bets and de-risk launches

Were looking for a senior backend engineer in our Tel Aviv office who gets excited about this stuff.

You'll be building the platforms that power everything from instant claims to personalized pricing. Think TypeScript with NestJS, all running on Kubernetes. But the cool part? Our own tools handle the boring stuff (deployments, environments, even git branches) so you can focus on the interesting problems.

In this role you'll:
Ship features that millions of customers will use

Work directly with the smartest PMs, Engineers, Designers, and Data Scientists in a zero bureaucracy environment

Own your domain end-to-end: write it, ship it, monitor it, improve it

Help other engineers level up

The GenAI team builds conversational experiences that feel human and decision engines that learn on their own. If moving from prototype to production with millions flowing through it gets you buzzing, keep reading.

In this role you'll:
Design, build, and own end-to-end Generative-AI services from first prompt to production rollout

Combine retrieval-augmented generation (RAG), function calling, and agents to automate underwriting, claims, and customer support flows

Fine-tune open-source and commercial LLMs on proprietary datasets, evaluate with both offline benchmarks and online A/B tests

Collaborate with product, data science, and design to invent new AI-first customer experiences (and kill the bad ones fast)

Build scalable APIs and micro-services (TypeScript/NestJS or Python/FastAPI) running in Kubernetes on AWS

Instrument, monitor, and continuously improve model quality, latency, and cost you ship it, you own it

Mentor fellow engineers on GenAI best practices: prompt engineering, vector search, safety & guard-rails

Contribute to internal tooling that automates the boring stuff (CI/CD, sandbox environments, branch deploys)

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of our primary product. This involves working on core systems, such as POS underwriting models, models for merchant operations, and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities:
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g., using SHAP values for model explainability and providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.