Were looking for a hands-on AI Engineering Tech Lead to define and drive AI-native engineering practices, lead the architecture and development of scalable, intelligent systems, and embed AI across the software development lifecycle. This role involves providing technical leadership, identifying and solving architectural challenges, and collaborating cross-functionally to deliver high-impact, production-grade solutions.


Responsibilities:
Define and codify AI-native engineering practices, patterns, and guidelines to elevate the software development lifecycle.
Provide technical leadership and mentorship, fostering an AI-first engineering culture across teams.
Architect and lead the development of AI-native system frameworks that emphasize modularity, extensibility, and adaptive scalability.
Identify architectural risks, systemic bottlenecks, and long‑term scalability concerns - and proactively drive solutions.
Collaborate closely with Product, Customer success, Security and Business stakeholders to ensure technical solutions deliver real business impact.

We are looking for a Staff Architect, Data & AI Infra to shape, build, and scale the infrastructure that powers our 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 our 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 our 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.

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 looking for a MLOps Team Lead.
As an MLOps Team Leader , you will own our AI infrastructure and backend engineering efforts, leading a team at the intersection of systems design and machine learning to build the engineering systems that turn Deep Learning and Computer Vision research into reliable, scalable production features.
What Youll Be Doing:
Lead MLOps Engineering: Own the roadmap and execution for a team of backend and AI infrastructure/MLOps engineers, setting technical direction, removing blockers, and holding the bar on delivery quality.
Build Production AI Systems: Design and implement production-grade, end-to-end AI solutions, including agentic workflows, that integrate Deep Learning models and Computer Vision algorithms into real features. Own the offline experimentation and validation layer, including POC environments that let the Algo team move from research to production confidently.
Architect Data Platforms: Drive the design and implementation of scalable data platforms and pipelines that power AI capabilities reliably and with an eye on cost and scale.
Cross-functional Collaboration: Work closely with the Algorithms and Data teams to tackle complex, real-world problems, translating research into shippable, maintainable systems.
Elevate Engineering Standards: Champion Software Engineering and System Design best practices across the group, introducing the right methodologies, tooling, and culture of craft.
Who You Are:

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions.
This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

Were growing fast and looking for an AI Security Team Leader to join our Engineering Team and play a key role in leading the development of our cutting-edge AI security products .
This is a high-impact, cross-functional role where youll work closely with Product, Design, and other Engineering teams, helping us deliver high-quality, customer-centric security solutions in a fast-evolving domain.
If youre highly accountable, adaptable, and business-value driven, and excited about cybersecurity, cutting-edge AI, and fast-paced startup challenges, wed love to meet you.
What Youll Be Doing:
Lead & Mentor: Lead a high-performing engineering team developing next-gen AI security products in a dynamic, rapidly changing domain.
Drive Value: Work closely with Product and customers to understand business requirements and transform them into robust, high-quality technical solutions.
Cross-Functional Ownership: Collaborate end-to-end with Product, Design, and other R&D teams to execute complex cross-company projects.
Technical Guidance: Provide architectural overview and technical mentorship to your team, stepping in when necessary to guide proper technical decisions and implementations.
Delivery & Quality: Own the execution, quality, and delivery of products running on endpoints and cloud environments in a high-velocity startup environment.

We are looking for an experienced Data Infrastructure Team Lead to lead our Data Infrastructure team. In this role, you will have formal people-management responsibility for a multidisciplinary team that builds, productionizes, and improves big data and analytics infrastructure. You will be responsible for team delivery, combining technical depth, agile leadership, and an AI-first mindset to help the team build reliable systems, improve how it works, and continuously raise its engineering standards.

Location: Ramat Gan (Bursa area), Israel - Hybrid model

What will you do?

Lead, manage, and develop a data infrastructure team of approximately 5-7 people.
Take responsibility for team delivery, including planning, prioritization, execution, and continuous improvement.
Lead agile ways of working, including scrum-based delivery practices.
Guide the design, productionization, and ongoing improvement of big data and analytics infrastructure.
Partner closely with cross-functional stakeholders across technical, scientific, and business interfaces.
Help the team adopt AI-first engineering practices, including automation and AI-assisted development workflows.
Drive improvements in team processes, technical quality, delivery predictability, and collaboration.
Support architectural and technical decisions across cloud infrastructure, data pipelines, orchestration, and production systems.
Create an environment where team members can grow, contribute, and improve together.

Were 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. 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.

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. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

we are hiring a Software Engineer to help revolutionize the world of observability. Using cutting-edge AI-driven technology, we are redefining how organizations monitor, analyze, and optimize their systems-making observability more intelligent, efficient, and accessible than ever before. As we scale, we seek top talent to push the boundaries of innovation and shape the future of AI-powered observability. If you're passionate about solving complex challenges and building game-changing technology, join us in transforming how the world understands and interacts with data.



Responsibilities:

End-to-end development and ownership of products and features, from design to scalable and predictable production behavior

Solve diverse and complex problems in a high-scale, cloud-native environment

Collaborate with other engineers and product managers to improve product functionality, scalability, and performance

Design, develop, and maintain robust, secure, and efficient software solutions

Ensure high system reliability by implementing best practices in monitoring, observability, and automation

Review code, architecture, and data to identify and troubleshoot technical and performance issues

Work with AI/ML teams to integrate AI capabilities, including model monitoring, evaluation, and fine-tuning