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What We Are Looking For As a VP of AI Security Research you will lead, scale, and inspire multi-disciplinary teams focused on red teaming, sandboxing, adversarial testing, developing red-teaming engines, and guardrail protections for GenAI models and agentic AI systems. In this high-profile role, you will work closely with security research, product, engineering, and compliance teams to shape and deliver the next generation of AI cybersecurity solutions, while combining strategic vision with execution to effectively safeguard LLMs and agentic AI deployments at scale. Key Responsibilities
* Building and scaling global AI security teams, while providing mentorship to senior managers and fostering an innovation-driven security culture.
* Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems, and delivering executive-level threat intelligence and risk assessments to inform corporate AI strategy.
* Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress-test models at scale.
* Partnering with product and engineering to design and deploy enterprise-ready AI guardrails, including policy enforcement layers, monitoring pipelines, and anomaly detection systems – and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).

About Alice:
Alice is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, Alice empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, Alice enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.

Hybrid:
Yes

Alice is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. We’re seeking an outstanding Backend Engineer with a Generative AI orientation to join our research team. We are building a new AI Platform from scratch to standardize AI development methods, ensure excellence and efficiency, and deliver robust, scalable, and compliant AI capabilities. This platform will handle GenAI models deployment, prompt management, data filtering, logging, and monitoring, centrally, so individuals can focus on their own business-specific logic. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.

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 partners with the world’s leading AI labs to deliver best-in-class model assurance, red teaming, evaluations, and post-training data programs. We’re looking for a Technical Engagement Lead to guide the technical success of these strategic customers. In this role, you’ll be the key technical counterpart to frontier-model teams—helping them design, structure, and execute complex AI safety programs. You won’t be building prompts or running evals yourself; instead, you’ll lead the technical architecture and orchestration of our work, ensuring quality, coherence, and impact across multiple workstreams. You’ll work hand-in-hand with a Senior Account Manager, delivery teams, researchers, and product leaders to help GenAI customers push forward safely and responsibly. What You’ll Do
* Serve as the primary technical partner for leading LLM labs and GenAI-native organizations
* Translate customer goals into structured evaluation, red teaming and data programs
* Design engagement architectures across multiple parallel contracts and initiatives
* Ensure technical excellence and consistency in all deliverables
* Lead technical discussions with research, safety, and product teams
* Identify risks, dependencies, and evolving needs early, and drive resolution
* Stay ahead of emerging evaluation methodologies, safety approaches, and model risk trends
* Partner internally with Delivery, Research, Product, and Account Manager to ensure seamless execution
Why Alice Work with the world’s leading AI labs
* Help shape the safety and trustworthiness of next-generation AI models
* Join a mission driven, high performing team
* Enjoy opportunities for growth and professional development in a cutting-edge field.
The salary range for this role is $150-200K OTE and stock options - Range may vary based on experience. Salary at the time of offer will be commensurate with experience.

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

CodeValue is looking for a highly motivated Full Stack Engineer to join our core engineering team and help us shape and build innovative products end-to-end. As part of a lean and agile R&D environment, you'll have real ownership — from design and architecture to implementation and deployment. You'll work across the stack: building scalable microservices and crafting modern, high-performance frontends. If you're passionate about delivering clean, scalable solutions that create real business impact — we want to meet you.

Were seeking a Staff Backend Engineer to expand and harden the core of Axioms platform. Youll work at the intersection of identity, security, and infrastructure, designing and delivering features that directly impact how Developers, Security, and Operational teams control access at scale.

This is a hybrid role based in Tel Aviv, where youll collaborate closely with engineering, product, and design to take features from concept to production quickly, securely, and at scale.

What youll be doing:
Design, develop, and optimize backend services that are performant, secure, and resilient.
Own end-to-end delivery of features: from design to deployment to monitoring.
Architect microservices and event-driven workflows in Go and AWS.
Collaborate across teams to transform ideas into production-ready systems.
Continuously improve scalability, reliability, and developer experience.
Mentor engineers and contribute to engineering culture through reviews and discussions.

As a Staff Software Engineer, you will play a critical role in building our platform. Your expertise and contributions will have a direct impact on the success and effectiveness of our product. Specifically, your responsibilities will include:
Lead, design, architect and build high-quality scalable software by introducing best practices around software engineering architecture and processes
Raise the bar on engineering excellence by improving standard methodologies, producing best-in-class code, documentation, testing, and monitoring
Collaborate with product and R&D engineers to translate product requirements into technical solutions.
Identifying and resolving technical issues and performance bottlenecks.
Staying up to date with the latest industry trends and technologies to continuously improve our products.
Be a mentor for colleagues and help promote knowledge-sharing.

This role requires working from the office four times a week.

We are seeking a visionary and hands-on AI Scientist to help shape the next generation of foundational language models and agentic systems that empower small and medium-sized businesses (SMBs) to thrive. In this role, you will play a key part in defining, designing, and building groundbreaking AI solutions that understand, reason, and act across complex financial and business contexts.
You will collaborate closely with cross-functional experts in AI research, data science, engineering, and product to create intelligent agents that help SMBs automate financial tasks, make smarter decisions, and operate more efficiently. Your work will combine scientific rigor with visionary execution, balancing theoretical innovation with large-scale practical impact.
The ideal candidate is a builder-scientist-a creative thinker who not only develops novel model architectures and training paradigms but also drives their implementation and validation in real-world applications. Youll have the opportunity to shape the AI foundation that powers transformative products serving millions of customers.
Responsibilities:
Design and develop foundational language models and agentic architectures that power intelligent decision-making for small and medium businesses.
Explore novel approaches in large-scale pretraining, fine-tuning, retrieval-augmented generation, and reasoning to improve factuality, adaptability, and alignment.
Build intelligent agents capable of understanding financial data, customer context, and business workflows - from bookkeeping and planning to communication and insights generation.
Collaborate with cross-functional teams across AI research, engineering, product, and design to translate breakthrough science into scalable products used by millions.
Define technical strategy and roadmap for next-generation agentic systems, driving innovation and excellence across the organization.
Publish and present research findings, internal innovations, or contributions to open-source frameworks where appropriate.

As a Senior Analyst on the Trust and Safety Analytics team, you will play a critical role in identifying, analyzing, and operationalizing key data signals to help prevent fraud, protect customers, and enforce acceptable use of products and services. You will apply strong analytical and technical skills to support and scale risk detection tools, monitoring processes, and mitigation strategies across Trust & Safety.
This role partners closely with Product, Engineering, and Operations teams to deliver insights that drive data-informed decisions and measurable risk reduction.
Responsibilities:
Partner with Engineering and Product teams to support the design, implementation, and maintenance of analytics tools, dashboards, and data pipelines that enable effective fraud and risk monitoring.
Analyze large, complex datasets to identify trends, anomalies, and emerging fraud patterns, translating findings into actionable recommendations.
Contribute to the ongoing improvement of Trust & Safety platforms, including monitoring performance metrics, assessing platform health, and identifying risk gaps or degradation.
Design and maintain dashboards and reporting (e.g., Tableau) to track fraud performance, operational efficiency, and risk exposure.
Ensure data quality and reliability by performing validation, testing, and monitoring of analytics outputs; proactively identify and escalate issues.
Support incident analysis and investigations by using data to identify root causes, quantify impact, and recommend mitigation actions.
Stay current on fraud trends, AI-driven abuse, and industry best practices, incorporating new insights into analyses and detection strategies.
Clearly communicate insights to both technical and non-technical stakeholders, influencing decisions through data-backed storytelling.

Join the QuickBooks B2B Group as a R&D Team Lead, managing and developing the Bill-pay experience!
In this role youll be part of an innovative team that creates the next generation of payment mechanism, helping small business to get paid faster.
If you love having stretch goals, real world challenges, and making customers incredibly happy whilst fostering your obsessive need for perfect code and user experience, this is the job for you.
You will collaborate with many teams in and contribute to many components in different Business Units.
We love engineers who lead the change, are not afraid of technical challenges, communicating with customers and delivering the most beautiful and intuitive applications.
Responsibilities:
Technology leaders think strategically and drive for results. They build high performing teams by putting the right people in the right job at the right time. Leaders help to innovate by thinking differently. They lead their teams to embrace new ideas that produce outstanding results for our customers. Leaders at inspire others thru action by creating a spirit of collaboration.
In this role you will help to bring out the best ideas from the best engineers by empowering them and leading by example.
Your team will create and bring customer driven software products to market that simplify and solve for current customer needs while building for the future.
To accomplish this you will create a shared vision and build and maintain strong cross-functional relationships / alignment with partners across the business (e.g. Program Mgmt, Business Analyst, Program Managers and Development Managers across the org).

Come join as a Senior Staff Machine Learning Engineer (MLE).
Senior Staff MLEs deliver end-to-end AI solutions that span multiple domains and products, influencing the strategic direction of machine learning and AI across the company. You will identify cross-cutting opportunities, set technical direction for complex systems, and deliver scalable, responsible AI-driven experiences that unlock customer and business value at scale.
In this role, youll be expected to define and evolve ML architecture, guide multiple teams, and drive execution excellence across the full ML lifecycle-from experimentation to production. Youll partner closely with AI scientists, product engineers, and business leaders to solve high-impact problems and pioneer new capabilities that advance AI-native platform.

As a Staff Analyst on the Trust and Safety Analytics team, you will be responsible for identifying, making available, and leveraging critical data elements to optimize ability to fight fraud, protect its customers and enforce acceptable use of products and services. Specifically, you will focus on applying your analytical skills to design, support and scale tools, processes, and strategies that proactively identify and mitigate risks across the organization.
Responsibilities:
Collaborate closely with Engineering and Product teams to design, implement, and maintain analytics frameworks, tools, and data systems that support effective data monitoring and risk management strategies, enabling informed, data-driven decision-making.
Take an active role in the analytics team's efforts to manage and enhance Trust and Safety platform capabilities. Provide timely insights and actionable recommendations to strengthen platform performance and address emerging challenges. Develop tools and systems to measure platform health and assess risks, including designing dashboards to track performance metrics, analyze trends, and identify areas that require attention or intervention.
Ensure analytics systems are consistently reliable, accurate, and available. Establish proactive monitoring processes and implement thorough testing to detect and address issues, minimizing system disruptions or delays.
Contribute to effective incident management by using analytics to identify root causes, provide actionable insights, and continuously improve platform risk mitigation solutions.
Stay abreast of the latest developments in AI, and integrate insights into your analysis to address emerging risks

We are looking for a strong hands-on Engineering Manager to lead the AI Productization team. You will lead a team that creates innovative products and platforms, ensuring AI capabilities are delivered to our customers at scale. You will act as a technical leader, mentoring engineers and applying technical expertise to challenging programming and design problems.
Respnsibilities:
Strategic Leadership: Collaborate closely with other teams to lead the strategy as well as drive the execution and bring it to life. Create a shared vision and build/maintain strong cross-functional relationships with partners across the business.
AI Delivery: Lead the delivery of backend as well as front end experiences, powered by state of the art AI technologies.
Build High Performing Teams: Bring out the best ideas from the best engineers by empowering them and leading by example. Build high-performing teams by putting the right people in the right job at the right time.
Hands-on Leadership: Participate in code reviews, design discussions, and hands-on coding to ensure the team delivers high-quality software.
Operational Excellence: Drive results by thinking strategically and ensuring the team follows Agile development methodologies.

Come join the team as a StaffBackend Engineer. We are a customer-obsessed, and our capabilities serve millions of customers; we innovate to create hyper growth to the customers and the business; using new technologies and driving new platform initiatives.
If you are passionate about building a world class platform, at a high scale, this is the opportunity for you!
Responsibilities:
You will seek to improve performance by refactoring existing services and flows
You will mentor more junior team members and help them learn and progress professionally.
You will collaborate with various stakeholders - product management, analysts, data engineers, customer success, and more.
You will contribute by owning the designing and implementing new features and enhancements and represent the team in the technical aspect during discussions and architecture roundtables
You will be hands-on, 70 - 80% coding
You will serve as the immediate go-to person within the team for any tech-related issue or discussion
Youll be a good listener, while also having strong opinions on what is right
Youll be fun to be around and work with

We are seeking a highly skilled Staff Fullstack Engineer to join our team. The ideal candidate will have a passion for developing high-quality, innovative software solutions and a strong familiarity with GenAI.
Responsibilities:
Frontend & Backend Depth: Design and implement scalable, modular, and secure services while creating integration-centric solutions using modern API technologies. Manage the full cycle of web service creation and consumption with ReST or GraphQL API modeling.
Full Stack Development: Design and develop web, software, prototypes, or proofs of concepts (POCs). Hands-on coding across the stack.
AI Integration: Designing systems with multi-step reasoning, using tool use and API orchestration to productize AI capabilities.
Cross-Functional Delivery: Work cross-functionally with various teams including product management and business units to drive forward results. Contribute to the design and architecture of the project.
Experience with Agile Development, SCRUM, or Extreme Programming methodologies.

We are looking for a Machine Learning Engineer (MLE) to work on building foundational language models and agentic AI systems that empower small and medium-sized businesses (SMBs) in their financial and operational journeys.
In this role, youll work alongside Machine Learning Engineers, AI scientists and product teams to build LLM based solutions for millions of small and medium busniesses around the world, and build foundational models, involving translate breakthrough research into production systems - designing, implementing, optimizing cost, latency, serving models that reason, act, and learn across real-world business contexts. Youll build scalable pipelines and infrastructure that drive impact on customers lives with the state-of-the-art AI from prototype to customer impact.
This is a unique opportunity for an engineer who thrives at the intersection of science and production, combining deep technical understanding of AI systems with the rigor and creativity needed to deliver robust, reliable, and high-performing products at scale.
Responsibilities:
Implement, optimize, and deploy foundation and agentic models for large-scale use in financial reasoning, decision support, and business automation.
Collaborate with MLE, AI scientists to operationalize research ideas, turning model architectures and training methods into efficient, production-grade implementations.
Design, build, and maintain ML pipelines for data ingestion, preprocessing, training, evaluation, and continuous improvement.
Optimize inference efficiency and model latency, ensuring production systems meet real-time performance requirements.
Contribute to retrieval, memory, and orchestration components that enable agentic reasoning and long-term context management.
Establish best practices for model monitoring, evaluation, and safe deployment, including automated testing and observability in production environments.
Drive applied innovation, bridging the gap between research prototypes and large-scale, reliable business solutions used by millions of customers.