לוח משרות דרושים AI Engineer

Required AI Engineering Team Lead - Applied AI Engineering Group
Tel Aviv Full-time
The Dream Job
It starts with you - a technical leader driven to build both the agentic AI platform and the engineering team behind it. You care about backend quality, platform reliability, and growing engineers through real ownership. We are AI-first across the board - every team builds and operates agents. You'll set the technical direction for the platform that makes this possible: agent orchestration frameworks, LLM gateways, evaluation infrastructure, tool-calling systems, and retrieval pipelines. Without this platform, agents don't ship - you own the layer that turns AI research into Sovereign AI products, deployed across cloud and on-prem environments. You stay close enough to the codebase to debug production incidents, unblock your engineers, and make sound architecture calls.
If you want to make a meaningful impact, join our mission and lead the team that builds the agentic AI platform driving Sovereign AI products - this role is for you.
The Dream-Maker Responsibilities
Architect and evolve the AI platform - agent orchestration, LLM gateways, context engineering pipelines, evaluation infrastructure, tool-calling systems, and retrieval pipelines - through RFCs, prototypes, and design reviews.
Lead and grow a small team of AI Engineers building the agent framework, production backend services, and AI platform infrastructure - hire, mentor, pair on hard problems, and raise the bar through hands-on code and design reviews.
Contribute to critical systems, debug production incidents, and maintain enough codebase context to make sound technical calls.
Own reliability across AI and agent services - set and enforce SLAs, build observability for non-deterministic systems, and harden tool execution environments for cost and security.
Set the standard for AI engineering practices - agent testing strategies, evaluation frameworks with human-in-the-loop oversight, retrieval quality benchmarks, and CI/CD for AI systems.
Work closely with ML Platform, Data Platform, DevOps, Data Science, and Product teams across the Applied AI Engineering group - ensure the AI platform evolves to serve teams building agentic workflows across the organization.
Measure and improve developer experience - deploy friction, onboarding time, CI turnaround - as seriously as system performance.

We are looking for a talented AI Algorithm Developer to join us in the research and development of our next-generation automatic sports video content engine. Our team operates at the intersection of Computer Vision, NLP, and Audio analysis. We dont just use models; we build multimodal pipelines that understand sports context like a human editor would.
If you are an expert in one of these domains (NLP, CV, or Speech) and are eager to master the others to build state-of-the-art Multimodal AI - we are looking for you!
What youll do:
Research and develop end-to-end real-time solutions for sports content automation using state-of-the-art Deep Learning (LLMs, VLMs, Audio models, and Generative AI).
Collaborate with Computer Vision and Audio experts to fuse different data signals into unified models.
Combine deep language models, Generative AI, and classical ML techniques to create high-quality solutions for demanding product-oriented tasks.
Manage the full R&D cycle: from problem definition and reading papers to implementation, prompt engineering, and productization with high autonomy.
Engage in collaboration with product and success teams to convert business goals into measurable algorithmic objectives.
Write robust, production-grade Python code that scales.

we are seeking an R&D AI PMO to support the execution of its AI strategy and transformation across Product and R&D. Reporting to the Head of Strategy and Operations for Technology and Product, the role will be responsible for identifying high‑value AI use cases across the software development lifecycle (SDLC) and institutionalizing the use of AI capabilities to deliver measurable improvements in development efficiency, quality, and business impact. Working closely with R&D and Product leadership, the role will drive adoption through training, documentation, knowledge sharing, and governance, while defining and tracking KPIs related to financial benefits, efficiency, and quality. This role is critical to the success of Sapiens AI transformation and requires strong technical acumen, hands‑on experience with modern AI development tooling (e.g., Claude Code, Rovo, GitHub Copilot), and proven experience leading technology‑driven transformation programs at scale.



Key Responsibilities:​
Support the implementation of the AI strategy across R&D by identifying, selecting, and institutionalizing AI tools to drive efficiency across the SDLC​
Partner with R&D and Product leadership to drive adoption of AI tooling, developing training materials, use cases, and leading enablement sessions across divisions/product teams​
Define and track KPIs to measure AI impact (e.g., financial benefits, development efficiency, quality improvements), providing visibility on realized value​
Establish and maintain governance frameworks, artefacts, and AI usage policies in collaboration with R&D Ops and SecOps to ensure structured and compliant adoption​
Identify operational risks related to AI adoption, driving mitigation plans and supporting governance forums to track progress and communicate with senior stakeholders​

we are looking for a AI Engineer Team Lead.
What will you do?
Own the agentic infrastructure- You're responsible for the architecture of Klaudia's core - the systems that make autonomous investigation, root cause analysis, and self-healing possible at scale.
Build and grow your team- Hire great engineers, mentor them, run meaningful design reviews, and build a culture of high ownership and engineering excellence.
Drive experimental development- Run structured bets - LLM evaluation frameworks, new agent architectures, novel tool-use patterns - and bring the best ones to production.
Stay hands-on You'll design systems, review PRs critically, and write code where it matters. Your technical credibility is the foundation of your leadership.
Shape our AI strategy- Work closely with product and R&D leadership to define what Klaudia becomes next.

we are looking for a Senior AI Backend Engineer.
Build the future of AI in the world of Cloud Infrastructure. You'll design innovative solutions powered by AI and help shape where we're headed as a company.
Why This Role Rocks:
Develop cutting-edge AI solutions - We're harnessing LLMs to solve real cloud infra problems, not just for buzzword points
We build the future - AI SRE became the hottest market in the cloud infra space - its our job to lead it.
Your ideas become reality - Propose solutions, lead initiatives, and see your impact
Shape our tech direction - You'll have a real voice in our technical strategy.
FULL Ownership: We believe in taking developments end to end. From ideation all the way to production.

We are looking for a Prompt Engineer to design, optimize, and continuously improve multi-turn conversational experiences across multiple product lines. This role combines linguistic creativity, AI prompt engineering, and real-world experimentation.
Youll work closely with product managers, who will provide requirements and prioritization, while you focus on crafting and iterating prompts, testing in real-world scenarios, and delivering natural, trustworthy interactions.
This role is based in Tel Aviv, with a hybrid work setup, combining in-office collaboration with remote flexibility.
Key Responsibilities:
Conversational Design and Prompting:
Design multi turn dialogue flows for text and voice agents with context awareness and memory handling. Define personalities and tone across products and agents.
Create multilingual prompt strategies and develop reusable templates and frameworks to speed development.
Continuous Testing and Improvement:
Test prompts with recordings, transcripts, and simulations before and after launch. Analyze live interactions to spot hallucinations, tone issues, dead ends, and token inefficiency.
Iterate quickly to improve quality, safety, and naturalness and use analytics and qualitative insights to measure success.
Collaboration and Delivery:
Partner with product managers on requirements and goals and work with engineers to integrate prompts within technical constraints.
Coordinate updates across multiple agents with version control for a unified experience and support compliance and privacy standards.
Documentation and Knowledge Sharing:
Maintain a prompt library with flows, system prompts, and version history and set guidelines for tone, multilingual consistency, and testing.
Share insights and learnings with the broader product and AI teams.

Design and execute research projects using advanced methodologies and tools to generate actionable insights that improve decision-making.
Analyze data and apply critical thinking to identify innovation opportunities and optimize research processes.
Prepare scientific reports and presentations to effectively communicate findings and recommendations to stakeholders.
Collaborate across teams and consult with experts, demonstrating adaptability, receptiveness to feedback.

We are looking for an experienced Deep Learning & AI Infrastructure Engineer to join our AI team. In this role, you will develop and deploy advanced deep learning models for signal processing and build the infrastructure and tooling required to scale AI training and inference in both research and production environments.
You will be responsible for the end-to-end lifecycle of AI workloads, including data ingestion and preprocessing pipelines, model training infrastructure, efficient inference systems, and automated experiment tracking.
Key Responsibilities
Design, implement, and optimize deep learning models and pipelines for signal and image analysis.
Build and maintain AI infrastructure components to support model training, versioning, monitoring, and deployment.
Develop scalable data processing pipelines for datasets, including ingestion, labeling, augmentation, and preprocessing at scale.
Implement automated training workflows using tools such as ClearML or other experiment tracking platforms, ensuring reproducibility and model governance.
Collaborate with system engineers to integrate AI models into real-time radar systems and ensure efficient inference performance.
Optimize distributed training and resource utilization.
Run performance tuning, testing, and benchmarking for both training and inference workloads.
Document infrastructure components, training procedures, and model lifecycle processes.

What Were About
we are a fast-growing startup at the forefront of application security. Our cutting-edge platform is designed to help development teams build secure software quickly, enabling them to move faster while managing risks. As pioneers in the AppSec space, were shaping the future of secure software development in the AI era. If you're looking for an exciting opportunity to make a significant impact and grow with a passionate team, we are the place to be.
About the Team
Our team is at the forefront of agentic AI - both within our company and across the broader Application Security space. We lead the development of AI-powered, agentic security capabilities within our ASPM product, driving innovation from early experimentation all the way to production, deployment, and continuous monitoring.
As a cross-functional team, we specialize in turning cutting-edge Machine Learning, Data Science, and agentic AI into scalable, real-world solutions that power our companys platform.
What You Will Do
Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, data scientists, and analysts.
Design, build, and optimize end-to-end AI-driven features and agentic workflows - from experimentation to validation and deployment (using Python and C#).
Develop scalable backend services to support production-grade agentic AI features.
Build and improve solutions powered by LLMs, AI agents, multi-agent systems and generative AI frameworks.
Evaluate agentic architectures and models performance, and contribute to monitoring, reliability, and continuous improvement in production.

As an Enterprise Professional Services Engineer, you are the technical architect and relationship lead for our most strategic global accounts. You own the technical success of the customer journey, focusing on Solution Design and the Integration Strategy required to make our company the heart of a modern IT stack.
This is a high-impact role for a consultant-engineer hybrid. You will be expected to leverage deep API architecture knowledge, advanced scripting, and creative problem-solving to design bespoke solutions that bridge the gap between our company and complex enterprise ecosystems. You are the "Bridge" between business requirements and technical reality.
Key Responsibilities
Integration Design & Scripting Excellence
Architect Integration Solutions: Lead the technical design of complex integrations using REST APIs and webhooks to seamlessly connect our company with enterprise stacks such as ServiceNow, Salesforce, Okta, and Azure.
Advanced Automation Scripting: Utilize PowerShell and Python to automate complex IT workflows, data migrations, and system synchronizations tailored to enterprise security and compliance standards.
Technical Strategy: Design end-to-end migration paths for Enterprise customers, moving them from legacy infrastructure to a modern, AI-first our company environment.
AI-Driven Workflows: Design and implement AI-driven automation logic that reduces manual overhead and optimizes operational efficiency for global IT teams.
Relationship & Project Leadership
Lead the Relationship: Serve as the primary technical point of contact, managing stakeholder expectations and translating high-level business goals into technical solution blueprints.
Project Execution: Own the full project lifecycle from a leadership perspective-ensuring on-time delivery, technical validation, and a "white-glove" customer experience.
Global Travel: Travel abroad up to 25% of the time to conduct on-site architectural workshops, lead high-stakes deployments, and build face-to-face rapport with strategic partners.
Communication
English - High proficiency: You must be able to present complex technical architectures to C-suite stakeholders with clarity, authority, and professional polish.
Solution Documentation: Produce high-quality architectural diagrams, technical implementation guides, and API mapping documentation.

We are looking for a hands-on AI Engineer to help build our core intelligence engine and infrastructure. In this role, you will work on exploring and building autonomous solutions that execute security workflows end-to-end, moving capabilities from research concepts to scalable production features.
What You Will Build:
● Internal AI Infrastructure: Contribute to a shared internal AI platform for models, data, training, and observability.
● Autonomous Capabilities: Build solutions that automate complex security operations and investigative workflows.
● Active Defense Mechanisms: Help productize runtime guardrails into customer-facing protective controls and monitoring systems.
Responsiblities:
● Develop and implement the engineering backend for AI-driven security features.
● Build and maintain the internal mechanisms that allow for safe and scalable AI feature deployment.
● Collaborate with AI Researchers to translate findings into production-grade autonomous workflows.
● Implement runtime guardrails and AI-focused data security capabilities.

We are looking for a visionary AI Lead to build our internal AI platform and architect adaptive intelligence systems that serve as a dedicated security architect for each of our customers. You will lead a team of AI Researchers and Engineers to move beyond simple integrations and build true autonomous security solutions.
Responsibilities:
● Lead the AI Research Group, managing AI Researchers, Engineers, and DevOps.
● Own the intelligence engine end-to-end, delivering next-generation analytics and contextual visualization features.
● Drive the strategic "build vs. partner vs. buy" decisions for cloud prevention and AI controls.
● Collaborate with the Threat Team to develop AI-driven threat detections against emerging attack vectors and novel AI threats.

Responsibilities
Partner with team leads to deeply understand workflows, challenges, and operational bottlenecks.
Identify opportunities for automation and AI enablement across teams.
Design and implement AI-powered internal tools and systems.
Build and maintain integrations between platforms (CRM, marketing tools, internal systems, etc.)
Develop lightweight applications and automated workflows.
Rapidly prototype solutions and iterate based on real usage.
Drive adoption and ensure solutions are practical and scalable.
Document processes and create repeatable internal standards.

Responsibilities
Design, develop, and maintain full stack features end-to-end-from frontend UI (Angular) through backend services (.NET / Node.js) to database and infrastructure.
Build and iterate on AI-powered product capabilities, including LLM-based coaching, conversation simulations, and intelligent analytics.
Work with LLM orchestration frameworks (e.g., LangGraph, LangChain) and cloud AI services (AWS Bedrock, OpenAI, Anthropic) to design reliable, production-ready AI pipelines.
Collaborate closely with product managers, designers, and backend engineers to translate requirements into high-quality, scalable solutions.
Design and develop responsive, performant frontend experiences using Angular, TypeScript, and modern component libraries.
Own the quality of your work-write tests, conduct code reviews, and continuously improve the codebase.
Evaluate and integrate new technologies, tools, and architectural patterns to keep our stack modern and efficient.
Troubleshoot and resolve complex technical issues across the full stack, including performance bottlenecks and integration challenges.

we are looking for a AI Architect.
Responsibilities
1. AI Architecture & Technical Leadership
Guide AI architectural direction across platform, focusing on system design, model lifecycle, and integration of AI components into product workflows.
Act as a senior technical reviewer and thought partner for complex or cross-team AI design decisions.
Provide technical oversight on areas such as exploring new models/technologies/opportunities for the company
Surface architectural risks, tradeoffs, and long-term implications, including cost, security and compliance aspects and clearly advise the VP of AI when certain technical directions should not be pursued.
This role influences judgment, clarity, and experience, not through blocking authority.
2. Hands-on Applied Innovation (Core Pillar | ~50%)
Spend at least 50% of time hands-on, building:
End-to-end AI prototypes
Technical demos and proofs of concept
Exploratory implementations of new AI capabilities
Drive applied innovation that:
De-risks new technologies
Demonstrates feasibility and impact
Informs product direction and business opportunities
Build fast, concrete examples that teams can learn from and extend.
Transition successful prototypes to team ownership for further development and scaling.
This role is expected to lead AI innovation by doing, while working closely with product, medical and engineering
3. Best Practices & Technical Enablement
Define and promote best practices for applied AI development, including:
Rapid prototyping and vibe coding.
Agent design, orchestration, and evaluation patterns
Experimentation, benchmarking, and validation workflows
Help teams align on shared technical patterns, tools, and standards.
Identify opportunities to consolidate duplicated efforts and improve cross-team coherence.
Lead technical deep dives, architecture discussions, and design reviews.
4. AI Compliance & Regulatory Enablement (Technical Scope)
Ensure AI development practices align with applicable AI regulations for a software product handling sensitive medical data.
Define and guide AI-specific compliance practices, including data usage, transparency, evaluation, and documentation expectations.
Support and contribute to AI-related compliance and regulatory documentation, in close collaboration with Legal, Security, and Medical Research teams.
Serve as a technical point of reference for AI compliance questions.