דרושים » AI » AI Knowledge Team Lead

Alice is building its internal AI infrastructure layer from the ground up. We have real agents running in production, a growing base of employees using AI in their daily work, and a clear architectural direction. What we don't have yet is a dedicated engineer to own it. You'll be the first. Your job is to close the gap between "working prototype" and "production platform" - owning the foundation that hosts our agents, the pipelines that ship them, and the reliability layer (observability, cost controls, audit trails, evals) that makes it safe to run AI at scale in a trust & safety company. This is an infrastructure-first role with deep AI fluency - not a prompt engineer, not a wrapper-framework operator, not a no-code builder. You should be equally comfortable writing a Terraform module, debugging a Kubernetes pod, and tracing an agent's tool-call chain. We don’t operate with a predefined backlog here; you will be responsible for identifying high-impact needs and bringing them to life. The perfect fit for this role has a track record of deploying agentic systems that have held up under real-world usage, balances a focus on infrastructure with a deep concern for user experience, and recognizes that the primary hurdle in AI integration is rarely the model itself. Responsibilities: Platform & Infrastructure
* Architect, build, and run the AWS/Kubernetes platform that hosts Alice's internal AI agents and tools; drive AWS Well-Architected pillars (operational excellence, security, reliability, performance, cost, sustainability).
* Own Infrastructure-as-Code: Terraform modules, standards, and reviews for Bedrock, agent runtimes, vector DBs, and supporting services. AI Systems
* Design and ship production-grade agents and multi-agent pipelines using the Anthropic Agent SDK, Claude Code, AWS Bedrock, and MCP — not wrapper frameworks.
* Own the full agent lifecycle: scoping ? prototyping ? eval ? deploy ? monitor ? iterate.
* Integrate agentic workflows into internal and product systems via APIs, databases, webhooks, Slack, and email. Reliability, Observability, Cost
* Build first-class observability across apps and infra: OpenTelemetry, Prometheus, plus LLM-specific tracing (Langfuse or equivalent), token/cost metrics, and eval pipelines.
* Define SLOs/SLIs and error budgets for AI services - latency, model fallback chains, eval regression gates, agent success rates. Lead incident readiness, response, and post-mortems.
* Drive FinOps: model routing by cost, cache hit rates, batch vs. realtime tradeoffs, budget alarms, per-team chargeback visibility.
* Implement guardrails: prompt-injection defenses, PII redaction, model allowlists, human-in-the-loop checkpoints, audit trails. Org Impact
* Identify high-leverage workflows across the organization and translate them into scalable agentic automations.
* Partner with R&D, Delivery, security, and external vendors to deliver platform capabilities.

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.

Hybrid:
Yes

Our Innovation team builds adversarial RL environments that train the worlds 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.
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
About us:
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, we provide 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 hands-on Business Systems & Automation Specialist to join our growing team. In this role, youll manage and optimize the business applications and integrations that power Candexs operations.
Youll be part of the team that owns the companys applications ensuring theyre well-maintained, scalable, and integrated to support business growth.
Youll be one of the go-to experts for building automations and workflows to streamline operations across departments such as Sales, Customer Success, Operations, etc...
Responsibilities:
Administer and maintain core business systems and SaaS tools.
Design, build, and manage automations, native integrations, and custom API scripts.
Partner with cross-functional teams to understand business requirements and translate them into efficient system solutions
Explore, test, and implement new technologies or integrations that can add value to the business.
Manage CRM configuration, data integrity, and automations to support sales and account management workflows.
Monitor system performance, troubleshoot issues, and ensure optimal reliability.
Identify opportunities to improve processes through technology and automation.
Document system configurations, workflows, and best practices.
Collaborate with IT & security to ensure compliance and secure integration across tools.

Required AI Algorithm Engineer - Localization Team
Ramat Gan
Full time
You will be part of our REM (Road Experience Management) department, which is responsible for the automatic High-Definition map-making process, which is a key technology in our autonomous driving and high-end Driving Assistance systems.
Vision-based localization is a key enabler for utilizing and creating the maps. Our group is responsible for aligning the map with the world, and reporting detected changes during the drive. Our technology is safety-critical, and the code has strict time and memory constraints as it operates in real time.
What will your job look like:
Develop and optimize computer vision and deep learning algorithms to accelerate data generation and labeling workflows for autonomous driving
Apply both classical computer vision techniques and modern deep learning methods to solve large-scale data challenges
Collaborate closely with development and annotation teams to enhance automation and ensure high-quality data
Own the entire lifecycle from prototyping to scalable deployment within internal pipelines and tools
Develop tools to evaluate and analyze algorithm performance, robustness, and operational efficiency.

As a Senior Backend Engineer, you will be a key contributor in designing, implementing, and optimizing our Backend Engine and application infrastructure. You will collaborate with other team members to ensure our applications are cloud-ready, scalable, and secure - enabling us to stay at the forefront of our industry. You will get a chance to work on a variety of technologies, in a dynamic and fast paced environment.

Responsibilities
Collaborate with cross-functional teams to design, develop, and deploy robust and scalable features for our cutting-edge data analytics platform.
Architect, implement, and optimize backend solutions using Python to ensure seamless data processing, storage, and retrieval.
Collaborate closely with product managers, data scientists, tech-leads to understand requirements, provide technical insights, and deliver high-quality solutions.
Continuously enhance the performance, scalability, and security of the platform and backend services through code reviews, testing, and optimization.
Stay up-to-date with industry trends and emerging technologies; proactively recommending and implementing improvements to enhance the platforms capabilities.

We are looking for an AI Engineer to play a central role in building, evaluating, and advancing our AI models. You will own and evolve our benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

Location: Ramat Gan (hybrid model).

What will you do?
Own & Evolve Benchmarking - Design, build, and maintain our benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

We are seeking a driven, detail-focused professional to become a vital part of our team as a Generative AI Analyst. In this role, you'll dive into the cutting-edge of technology, meticulously analyzing various content infringements to secure the new wave of Generative AI tools. Your duties will include collaborating with experts in diverse fields such as Hate Speech, Misinformation, Intellectual Property and Copyright, Child Safety, among others.

Your tasks will involve writing adversarial; prompts to identify weaknesses in various AI models, including Large Language Models (LLMs), Text-to-Image, Text-to-Video, and beyond. You'll also oversee data management to guarantee the highest quality of outputs.

Responsibilities:
Developing adversarial and risky prompt strategies across several areas of abuse to expose potential vulnerabilities in models.
Managing projects end-to-end, from initial planning and oversight through quality assurance to final delivery.
Handling extensive datasets across multiple languages and areas of abuse, ensuring precision and meticulous attention to detail.
Ongoing investigation into new tactics for circumventing foundational models' safety measures.
Working alongside diverse teams, engineering, product, policy, to tackle new challenges and craft forward-thinking strategies and resolutions.
Promoting a culture of knowledge exchange and continual learning within the team.

As a Senior DevOps Engineer, you will be a key contributor in designing, implementing, and optimizing our cloud-native DevOps infrastructure. You will collaborate with other team members to ensure our applications are cloud-ready, scalable, and secure, enabling us to stay at the forefront of our industry.

Responsibilities
Cloud-Native Strategy: Develop and implement a cloud-native strategy, leveraging AWS, serverless, and other cloud-native technologies, to enhance application resilience and scalability.
Container Orchestration: Lead efforts to manage container orchestration platforms (e.g., Docker) and establish best practices for containerization and microservices.
CI/CD Pipeline Optimization: Enhance and automate our CI/CD pipelines to enable rapid and reliable software delivery, incorporating industry best practices and tools.
Infrastructure as Code (IAC): Drive the adoption of IAC principles and tools (e.g., Terraform, Ansible) to manage infrastructure provisioning, monitoring, and security.
Collaboration: Collaborate closely with software engineers to solve complex problems and drive continuous improvement.

We are seeking a driven, detail-focused professional to become a vital part of our team as a Generative AI Analyst. In this role, you'll dive into the cutting-edge of technology, meticulously analyzing various content infringements to secure the new wave of Generative AI tools. Your duties will include collaborating with experts in diverse fields such as Hate Speech, Misinformation, Intellectual Property and Copyright, Child Safety, among others.

Your tasks will involve writing adversarial; prompts to identify weaknesses in various AI models, including Large Language Models (LLMs), Text-to-Image, Text-to-Video, and beyond. You'll also oversee data management to guarantee the highest quality of outputs.

Responsibilities:
Developing adversarial and risky prompt strategies across several areas of abuse to expose potential vulnerabilities in models.
Managing projects end-to-end, from initial planning and oversight through quality assurance to final delivery.
Handling extensive datasets across multiple languages and areas of abuse, ensuring precision and meticulous attention to detail.
Ongoing investigation into new tactics for circumventing foundational models' safety measures.
Working alongside diverse teams, engineering, product, policy, to tackle new challenges and craft forward-thinking strategies and resolutions.
Promoting a culture of knowledge exchange and continual learning within the team.

As a Data Analyst, you'll be instrumental in constructing and managing the AI rules engine, alongside pinpointing network patterns to deliver value across various domains for our clients.
This role requires proficiency in deriving insights from data and conducting thorough analyses. Additionally, it offers significant autonomy for innovation and creativity, qualities we encourage in all team members. Strong teamwork and interpersonal skills are also crucial for success in this position.
Together, we can shape the future of network security.

Responsibilities:
Take a significant part in data analysis, contributing to our ever-evolving automation engine.
Research various network behaviors and patterns.
Preform data research to classify network entities based on behaviors and patterns.
Write and implement creative scripts to achieve data science-oriented goals.
Characterize and define new product features.
Work closely with Data Engineering teams to ensure the optimal solution is built in terms of logic and infrastructure.