דרושים » הנדסה » AI Engineering Tech Lead

We're looking for an experienced hands-on Software Engineering Team Lead to lead a highly skilled team of backend and frontend engineers through implementation, delivery, iteration, and build scalable systems that serve our customers.
Responsibilities:
Foster a positive, collaborative culture and grow the teams capabilities.
Lead and mentor engineers to ensure on-time delivery, quality development, productivity, and efficiency by conducting and lead design reviews & code reviews.
Work together with product managers to translate requirements into scalable technical solutions.
Balance refactoring and evolution with steady delivery of new features.
Drive a culture of technical excellence, ownership, and continuous improvement.
Oversee system reliability, monitoring, performance optimization and incident response.

We are seeking an experienced and highly motivated Team Lead to lead our Data Infrastructure team. This role is responsible for managing a team of engineers while driving the design, scalability, reliability, and operational excellence of the companys core data platform.
The ideal candidate combines strong technical expertise in distributed systems and data technologies with proven leadership capabilities, strategic thinking, and the ability to lead complex initiatives end-to-end - from initial design and planning through implementation, deployment, and production ownership.
Key Responsibilities:
Lead, mentor, and develop a team of Data Infrastructure engineers, fostering a culture of ownership, collaboration, and continuous improvement
Define and execute the technical roadmap for the organizations data infrastructure platform
Oversee the architecture, scalability, reliability, and performance of large-scale data systems and pipelines
Define and drive data quality standards, monitoring, and validation processes to ensure trust and reliability across the data platform
Partner with engineering and product teams to enable scalable data foundations for analytics, machine learning, and AI-driven initiatives
Lead cross-functional technical initiatives end-to-end, including requirements gathering, architecture design, implementation, deployment, and post-production ownership
Partner closely with cross-functional teams including Data Engineering, Analytics, Backend Engineering, DevOps, and Product Management
Drive operational excellence through monitoring, observability, automation, and incident management best practices
Ensure high availability and stability of critical production systems
Lead technical design discussions, architecture reviews, and engineering planning processes
Establish and promote engineering standards, development best practices, and quality assurance processes
Manage project prioritization, resource allocation, and timely delivery of strategic initiatives
Support recruitment, onboarding, performance management, and career development of team members
Evaluate emerging technologies and recommend improvements to the data platform ecosystem.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers data, AI, and research platforms. This is a senior player-coach role with broad architectural ownership across data infrastructure, ML infrastructure, developer experience, reproducibility, and production reliability. You will work across the wider engineering group as a hands-on technical architect, while also managing a small team of individual contributors focused on ML infrastructure.

This role is ideal for someone who can move between long-term platform architecture and practical execution: defining standards, building core systems, mentoring engineers, improving reliability, and partnering with Data Engineering, AI/Research, Product Engineering, Security, Bioinformatics, and Leadership to make data and AI platforms scalable, reproducible, secure, compliant, and easier to use.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Architectural Leadership: Own and evolve the technical roadmap for data and AI platforms, ensuring scalable and reliable architecture that supports current needs and prepares for a multi-cloud future.
MLOps & Platform Development: Design and build end-to-end MLOps systems-covering experimentation, training, reproducibility, and deployment-while managing specialized infrastructure like BigQuery, orchestration tools (Dagster/Airflow), and R/Python workloads.
Infrastructure Strategy: Define and lead strategy for GPU resources (scheduling, utilization, batch compute) and establish engineering best practices, data architecture standards, and platform guardrails.
Developer Experience: Enhance developer productivity by building self-service platforms, automation, internal tooling, and reusable templates that simplify workflows and reduce operational friction.
Team Leadership: Act as a player-coach to mentor engineers and manage a small team of ICs, fostering a culture of sound decision-making and technical excellence across the broader group.
Security & Reliability: Partner with Security to enforce compliance (SOC2, HIPAA, GDPR) and access controls, while mitigating operational risk through improved observability, incident readiness, and robust support processes.

Required Technical lead, Cloud Security
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Ramat Gan, Israel; Tel Aviv, Israel.
About the job
Our Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
In this role, you will guide the transition to an Artificial Intelligence (AI)-native Security Operations Center (SOC). You will guide a talented team in architecting the next-generation Agent Engine and universal Application Programming Interfaces (APIs) that empower enterprise security teams to orchestrate defense at machine speed. You will have an impact on how global enterprises defend against threats using our AI capabilities. You will play a role in shifting the industry paradigm from static workflows to changing, collaborative multi-agent ecosystems, while establishing a culture of engineering excellence that balances code quality with rapid developer velocity.
Responsibilities
Lead the technical architecture and design for the Security Operations (SecOps) Security Orchestration, Automation, and Response (SOAR) Group.
Drive the platform transition from bespoke playbooks to a AI-native SOC leveraging hybrid automation.
Drive direction and technical leadership for the Response group teams, promoting a culture of engineering excellence that balances rapid development velocity with uncompromising code quality and system reliability.
Provide overarching technical leadership, mentorship, and direction to a group of engineers building the multi-agent framework.
Ensure reliability, scalability, and secure API governance across the universal agent marketplace and distributed systems.

Join our innovative team at our company, where you will lead a talented Deep Learning R&D team developing advanced neural networks that are essential for our companys key products.
In this role, you will lead a team responsible for developing real-time vision models that power the vehicles understanding of its environment. The team combines research, hands-on development, model training, data analysis, optimization, and product-grade delivery for autonomous driving technologies and advanced driver-assistance systems.
As a Deep Learning R&D Team Lead, you will be responsible for both the technical and managerial leadership of the team. You will guide the full development cycle of deep learning solutions - from understanding the problem and data, through modeling and training, to performance improvement, validation, and delivery into production systems.
The role is ideal for someone who is technically strong, creative, independent, and motivated by solving complex, open-ended problems while leading people and driving execution in a fast-paced, product-oriented environment.
What will your job look like?
Lead a small and highly capable Deep Learning R&D team working on real-time computer vision models for our companys products.
Provide technical leadership across the full deep learning development cycle, including data understanding, model design, training, evaluation, optimization, and production readiness.
Drive goal-oriented research and development, balancing innovation with practical product needs, timelines, and delivery quality.
Mentor, support, and develop team members, while creating a strong professional environment that encourages ownership, creativity, and continuous improvement.
Break down complex and ambiguous problems into clear work plans, priorities, milestones, and execution steps.
Collaborate closely with cross-functional teams to understand requirements, align expectations, and deliver effective solutions.
Improve existing models and development flows to enhance accuracy, robustness, runtime performance, scalability, and product impact.
Stay up to date with the latest advancements in deep learning, computer vision, AI architectures, and AI-based development tools, and apply relevant ideas to improve the teams work.

We are looking for a highly skilled and motivated Software Team Lead to drive the technical direction of our development team while maintaining a substantial hands-on contribution. This role involves leading the team, hiring top talent, and ensuring the successful delivery of high-quality software solutions.
Responsibilities:
Technical Leadership: Guide the team in designing, developing, and maintaining robust cybersecurity solutions using Golang, C#, and Python.
Hands-On Development: Write high-quality, scalable, and secure code (50% of the time).
Team Management & Growth: Hire, mentor, and grow a team of talented engineers to build innovative cybersecurity products.
Code Reviews & Best Practices: Ensure high code quality through reviews, technical mentorship, and the enforcement of best practices.
Collaboration: Work closely with product managers, security researchers, and other stakeholders to define and deliver features.
Technical Roadmap: Contribute to architectural decisions and shape the future of the company's technology stack.

Alice’s Innovation team builds adversarial RL environments that train the world’s most advanced AI models to be safer. Our customers are the leading frontier AI labs, who use these environments for post-training reinforcement learning and safety evaluation. This is the bleeding edge of AI safety technology: the environments you build will directly shape how next-generation models learn to resist adversarial attacks. We’re 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. You’ll lead a small team (including a dedicated web environments engineer), operating with high autonomy, moving fast from concept to working prototype to production system. You’ll 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. You’ll be at the center of advancing AI safety, building systems that the world’s 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. There’s no playbook. You’ll write it. What you’ll 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

About Alice:
Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact—whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection.

Were looking for a Principal 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.

Required Data Engineering Manager
Data, Ramat Gan, Israel (Hybrid)
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.