דרושים » הנדסה » AI Architect

Required AI Architect
Position Overview:
As the AI Architect for our SaaS Platform & Products, you will define and drive the end-to-end AI architecture that powers our cloud AI platform and product capabilities, while ensuring strong alignment with security, privacy, reliability and cost-efficiency requirements. You will partner closely with engineering leaders, product management, data science, security and operations to translate business needs into a scalable, governed and AI platform that accelerates innovation across multiple product lines.
This is a hands-on architecture role: you will set technical direction, run architectural reviews, and build prototypes to validate technology choices and de-risk delivery.
Key Responsibilities:
Own the AI Vision: Take end-to-end ownership of the AI architecture across, including our cloud AI platform, agentic AI infrastructure, and on-prem/hybrid AI deployments.
Architect an AI Platform for SaaS Products: Define reference architectures and shared building blocks (e.g., AI gateways, orchestration runtimes, memory/RAG systems, vector search, evaluation frameworks, observability, and guardrails) that can be adopted consistently across products and teams.
Cost Optimization and Scalability: Provide architectural leadership to ensure AI systems are designed for cost efficiency and scalability, actively identify and implement opportunities to optimize cloud spend (FinOps), improve utilization, and meet latency/SLO targets.
Product-Centric Collaboration: Collaborate with engineering, product, data science, security, and operations teams to translate product requirements and business needs into a strategic AI architecture that drives measurable product value.
Technology Evolution and Prototyping: Evaluate new technologies, tools, and methodologies to continuously improve our AI systems, build prototypes and proof-of-concepts to validate approaches and accelerate decision-making.
Technical Reviews, Standards and Mentorship: Lead technical design reviews and provide guidance on best practices and emerging technologies. Act as a technical authority and mentor, fostering a culture of engineering excellence and pragmatic delivery.
AI Governance, Privacy and Security: Ensure AI capabilities comply with data privacy, security, and ethical AI guidelines. Partner with security and legal stakeholders to implement governance controls and risk mitigations appropriate for regulated environments.

Were seeking a visionary Team Lead to lead a AI & backend-focused team building our next-generation Generative AI Platform. This platform will empower cross-functional teams across our company to design and deploy AI-driven solutions, leveraging cutting-edge advancements in generative AI, cloud-native architectures, and rapid innovation cycles.
In this role, youll manage a high-performing backend team responsible for building scalable microservices and cloud-based infrastructure, while integrating advanced AI capabilities such as evaluation frameworks, RAG pipelines, knowledge base management, embeddings, LLMs, chatbot assistants, and agent orchestration.
What Youll Do
Lead and mentor a backend engineering team developing a scalable, cloud-native AI platform. Youll foster a culture of technical excellence, collaboration, and ownership while ensuring delivery of robust, production-grade systems.
Define the technical direction and architecture for backend services, focusing on microservices, distributed systems, and AWS-based infrastructure to support AI-driven applications.
Integrate cutting-edge AI capabilities into the platform, including RAG pipelines, embeddings, LLM orchestration, and evaluation frameworks, ensuring performance, scalability, and security.
Collaborate with product and engineering teams to translate business needs into backend solutions that enable AI-agent use cases and accelerate innovation across the organization.
Drive agile processes and best practices, leveraging tools like Jira to manage sprints, track progress, and continuously improve team efficiency and delivery quality.
Scale the team strategically, hiring and onboarding top talent while mentoring future leaders to support the growth of the Gen AI Platform group.

Were seeking a visionary and technically hands-on AI Team Leader to join and take charge of driving innovation across our core AI systems.
As the AI Team Leader, you'll guide the architecture and development of advanced machine learning models that power our video and creative analysis platform.
You will collaborate cross-functionally with product managers, engineering, and business development teams to deliver cutting-edge features that push the boundaries of whats possible in creative performance analysis.
This is a high-impact role for someone who thrives at the intersection of machine learning, product strategy, and creativity.
Key Responsibilities:
Lead the development, deployment, and optimization of machine learning models for video, image, and creative performance analysis.
Architect scalable AI/ML pipelines and infrastructure that support real-time and batch processing of multimedia data.
Guide research and experimentation initiatives-identify new technologies, modeling techniques, and opportunities for innovation.
Mentor and grow a team of machine learning engineers and data scientists as we scale.
Champion AI ethics, fairness, and explainability in our model development and deployment.
Stay ahead of industry trends in generative AI, computer vision, NLP, and Martech innovation, translating insights into competitive advantages.

The Staff Data & AI Architect will define and own the end-to-end architecture of our companys data and AI platform, spanning large-scale data systems, ML experimentation infrastructure, and production-grade model deployment. This role sets the architectural vision and technical standards for data and AI infrastructure across the company, ensuring scalable, compliant, research-accelerating systems that power both research and product development in a regulated biomedical environment.
Location: Ramat Gan, Israel (hybrid model)
What will you do?
Architect and evolve a scalable, resilient, and secure data and AI infrastructure supporting our companys research and product platforms. Identify recurring infrastructure and workflow challenges to drive the creation of generalized, reusable platform solutions.
Define scalable experimentation and MLOps patterns supporting experiment tracking, compute orchestration, dataset versioning, and reproducibility guarantees.
Lead the design and implementation of enterprise-grade data management. Establish and enforce data principles (e.g., FAIR, Medallion/Lakehouse architectures) to ensure data quality, lineage, discoverability, and reuse, while guaranteeing that all infrastructure meets security, privacy, and regulatory requirements.
Serve as the senior technical authority for data and AI infrastructure, partnering with Research, Engineering, and Product leadership to align architectural decisions with scientific and business priorities.
Lead technology evaluation and adoption decisions for AI infrastructure, balancing scalability, cost efficiency, compliance, and long-term maintainability.

We are seeking an experienced Software Architect to lead the design and evolution of our modular, component-based platform. This role is central to shaping scalable, maintainable, and future-ready backend systems as we modernize existing solutions and develop new ones. You will own architectural direction, define and enforce technical standards, and collaborate across teams to align design decisions with business, operational, and product goals.
The role focuses on system design, technical governance, and documentation, with hands-on contributions to PoCs, prototypes, and MVPs where needed.
Responsibilities:
Design and document scalable, modular backend architectures that support componentized platform development.
Lead architecture reviews and provide actionable guidance to development teams.
Define, provision, and enforce architectural standards, patterns, and governance practices across teams.
Support system modernization and greenfield development initiatives.
Ensure architecture decisions are aligned with long-term product strategy and evolving toward SaaS-based delivery.
Collaborate with Product, DevOps, QA, and Data Engineering teams to align architecture with cross-functional needs.
Contribute hands-on to early-stage initiatives (e.g., PoCs, architectural spikes, MVPs) to de-risk implementation paths.
Design systems with security, auditability, observability, and operational resilience in mind.
Promote engineering best practices, CI/CD adoption, and high-quality coding standards across the organization.
Incorporate and encourage the use of AI-assisted development tools to improve efficiency, consistency, and innovation.

Required AI Engineering Team Lead
Tel Aviv-Yafo, Gush Dan, Israel
We offer the industrys only platform that fuses customer identity and anti-fraud solutions - customer identity management, identity verification, and fraud prevention.
We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.
About the Role:
As the AI Team Lead, you will guide a team of highly skilled machine learning engineers in developing and deploying advanced AI/ML solutions that power our identity and security products. Youll combine technical depth with leadership skills to drive innovation, ensure delivery of high-impact projects, and scale our data-driven capabilities across the organization.
This role requires both strategic thinking and hands-on expertise. Youll be responsible for shaping the data science roadmap, mentoring a growing team, and collaborating with product, engineering, and business stakeholders to translate business challenges into practical machine learning solutions.
What youll do:
Leadership & Team Management:
Lead, mentor, and grow a team of machine learning engineers and data scientists.
Foster a culture of technical excellence, collaboration, and continuous learning.
Define team goals, measure progress, and ensure high-quality deliverables.
Strategy & Roadmap:
Own the data science strategy and align it with company objectives.
Identify opportunities for applying machine learning and generative AI across products and internal systems.
Evaluate emerging technologies, tools, and methodologies to keep the team ahead of the curve.
Hands-On Technical Work;
Design, prototype, and implement ML models, including LLM-powered copilots, retrieval systems, and fraud detection pipelines.
Guide the deployment of models into production environments with scalability and reliability in mind.
Ensure best practices for experimentation, evaluation, and monitoring.
Cross-Functional Collaboration:
Work closely with engineering to integrate ML components into production systems.
Partner with product managers to align solutions with customer needs and business priorities.
Collaborate with security and compliance teams to ensure ethical and secure use of data.

Our mission is to protect every mobile app in the world and the people who use mobile apps in their lives and at work.
We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform, delivering rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system.
With us , mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from inside mobile DevOps and CI/CD pipeline.
Leading financial, healthcare, m-commerce, consumer, and B2B brands use us to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and mobile businesses globally. Today, our customers use their platform to secure over 50,000+ mobile apps with protection of over 1B mobile end users projected.
We are seeking a driven and results-oriented Account Executive to join our team. In this role, you will focus on acquiring new customers, building trusted relationships, and driving revenue growth by understanding prospects mobile business and security objectives and aligning them with our solutions.
The ideal candidate is a proactive communicator with strong interpersonal skills and a solid technical foundation. You excel at managing complex enterprise sales cycles and thrive in a dynamic environment that demands collaboration across teams and effective engagement with stakeholders via phone, email, and in-person interactions.?About the Role
We are building an AI-driven future, and we need an exceptional AI Engineer to join our new AI Department. This is a unique opportunity to work in a startup environment within a growing company, where youll take ownership of AI and ML initiatives, build cutting-edge solutions, and influence the direction of our AI products. The role has strong leadership potential and is suited for individuals who are passionate about solving complex problems and making a real impact.
?What Youll Do

* Research, design, and implement LLM-based products and infrastructure.
* Collaborate with data scientists, data engineers, product teams, and backend engineers to integrate AI solutions into products.
* Take full ownership of AI engineering pipelines from experimentation to production.
* Utilize cloud-based AI deployment strategies, particularly within AWS.
* Develop and maintain high-quality, scalable, and efficient code.

We are seeking We are seeking an experienced Senior Generative AI Engineer (LLMs & Agents) to join our AI squad at KPMG. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work.
You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms.
You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities:
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Pytho
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliability, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures
Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders
Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS
Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.)
Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques
Define and refine best practices for GenAI system development and deployment
Contribute to internal accelerators, methodologies, and knowledge sharing

We are seeking a Backend Team Lead to spearhead the development of ludeo.ai, our GenAI-powered product that enables users to generate interactive (gaming experiences) directly from prompts or video content. This is a high-impact leadership role at the intersection of backend architecture, multimodal AI, and real-time systems. You will architect and lead the AI engine that transforms unstructured inputs (text/video) into structured, interactive gaming playable moments.

What Youll Do

Lead & Mentor: Build and manage a high-performing backend/AI engineering team, drive architectural decisions, and foster rapid innovation while maintaining production-grade reliability.
Design AI-Native Systems: Architect scalable microservices powering complex AI workflows. Design and implement Retrieval-Augmented Generation (RAG) pipelines, embedding strategies, and vector database infrastructure (e.g., Pinecone, Weaviate, Milvus, PGVector). Optimize retrieval, prompt orchestration, latency, and cost.
Agentic Workflows: Design multi-agent systems using planner/executor/tool-calling patterns. Implement stateful, multi-step AI workflows with frameworks such as LangChain, CrewAI, AutoGen, or similar. Build evaluation, observability, and safety mechanisms for LLM systems.
Multimodal AI: Integrate multimodal models (vision + text) to understand video and translate it into structured form.
Scale & Infrastructure: Ensure robustness, security, and high availability on AWS/Kubernetes. Design distributed systems that handle real-time data and AI workloads efficiently.
Collaborate: Work closely with Product and Design to translate GenAI capabilities into stable, scalable production features.