Jobs at Alice (Formerly ActiveFence)

Creates and evaluates adversarial attacks against LLMs and AI systems, including prompt injection, jailbreaks, agent manipulation, and tool-use attacks. Develops scalable attack-generation systems, benchmarks, datasets, and regression tests; assesses attack quality and model vulnerabilities; and communicates findings to data science, security, and engineering teams to improve AI robustness.

Leads a team of fraud threat analysts conducting OSINT and WEBINT investigations across web, mobile, social media, forums, apps, and the dark web. Sets research priorities, oversees technical validation of abuse scenarios, builds investigative tooling and research environments, analyzes datasets and telemetry, applies OPSEC, and delivers actionable fraud intelligence and mitigation guidance to clients and stakeholders.

Leads fraud threat analysts conducting OSINT and WEBINT investigations across web, mobile, social media, forums, apps, and the dark web. Sets research priorities, oversees technical validation of abuse scenarios, and develops investigative environments and tooling. Analyzes datasets, telemetry, and technical artifacts to identify fraud tactics and vulnerabilities, while delivering actionable mitigation guidance to clients and stakeholders.

Lead post-training evaluation, red-teaming, and reinforcement-learning gym audits for open-weight AI models. Execute GRPO and PPO training runs, analyze reward diagnostics and rollout traces, audit multi-turn tool-use environments, develop benchmarking methodologies, produce evaluation cards, and integrate Dockerized environments into distributed training frameworks. The role focuses on identifying security weaknesses such as indirect prompt injection, reward hacking, flawed verifiers, and unrealistic task designs.

Lead cyber threat research by hunting, detecting, and monitoring threats; analyze threat groups, actors, TTPs, and fraudulent ecosystems across clear, deep, and dark web sources. Produce technical intelligence reports, assess emerging threats, enrich analyst tradecraft, and brief clients and stakeholders. The role requires expertise in anti-bot or proxy research, web scraping, technical CTI hunting, OSINT/WEBINT, and cybercrime intelligence.

Lead technical cyber threat research, hunt and monitor threats, analyze threat actors and TTPs, research clear, deep, and dark web sources, and produce client-facing intelligence reports. The role also reviews analyst tradecraft, enriches intelligence, assesses emerging threats, and collaborates with account leads and stakeholders. Required expertise includes anti-bot or proxy research, web scraping, threat hunting, OSINT/WEBINT, darknet intelligence, and threat intelligence platforms.

Adversarially test and strengthen Generative AI models against cyber-CBRNE threats by designing red-team prompts, jailbreaks, multi-turn attacks, and scenario-based evaluations; develop test suites, taxonomies, and actionable mitigations while documenting vulnerabilities and maintaining threat and AI-safety expertise.

Lead and mentor a malware research team while conducting hands-on malware analysis, detecting emerging threats, improving research quality, and developing scalable automation. Responsibilities include recruiting and training researchers, evaluating performance, documenting malware trends, collaborating across teams, and enhancing analysis and review processes. The role requires experience in malware research, reverse engineering, penetration testing, SOC/IR, application security, programming, debugging, and network communications.

Own multiple AI lab delivery engagements from scope through shipment. Translate customer specifications into task plans, manage milestones and project status, allocate researchers and reviewers, oversee onboarding and quality feedback, and ensure batches pass internal review before delivery. Identify schedule risks early and recommend scope, capacity, or timeline tradeoffs. The role requires autonomy, cross-functional coordination, contributor management, and comfort operating in undefined, rapidly changing technical environments.

Lead the rapid development and release of AI safety and security benchmarks. Own evaluation taxonomies, harnesses, quality standards, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelance subject-matter experts. The role also requires reviewing research, engaging with frontier labs, presenting findings, and attending industry conferences.

Lead the development and release of AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, verification, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelancers. The role also requires staying current with AI safety research, maintaining lab relationships, presenting work to clients, and attending conferences.

Lead the development and release of frontier AI safety and security benchmarks every two to three weeks. Own evaluation taxonomies, harnesses, quality standards, publication decisions, research timelines, and quarterly roadmap planning. Collaborate with AI labs, universities, internal researchers, and freelance subject-matter experts. Conduct hands-on evaluation review, maintain ecosystem relationships, present research to clients, and attend conferences.

Principal-level hands-on engineer embedded in a product pod to drive 0-to-1 innovation. Responsibilities include architecting, coding, and launching greenfield products; creating demos and proofs of concept; leading high-stakes technical client discussions; shaping roadmaps and integration specifications; identifying automation opportunities; and resolving critical engineering bottlenecks. The role requires exceptional system design, modern AI expertise, commercial judgment, client presence, autonomy, and experience shipping complex software from scratch.

Serve as the senior technical front line for frontier AI lab clients in the Bay Area. Lead technical discovery, RFPs, solution scoping, client meetings, events, and technical discussions with engineering and research teams. Build the Valley AI and security community, represent the company publicly, translate market signals into research and product strategy, and help establish the company’s regional presence. Partner with sales on technical wins while influencing AI security research, product direction, and local hiring.

Lead post-training evaluation, red-teaming, and reinforcement-learning gym audits for open-weight models. Build benchmarking and evaluation pipelines for LLM security threats such as indirect prompt injection, analyze reward diagnostics and rollout traces, audit agentic environments, produce evaluation cards, and integrate Dockerized environments into distributed training frameworks. The role requires expertise in RL training, AI security, PyTorch, containerization, verifiers, reward shaping, and agentic tool-use workflows.

Lead and grow a multidisciplinary Data Science engineering team building real-time content moderation, GenAI safety and red-teaming systems, and Databricks-based data and MLOps platforms. Set technical direction, own delivery and quality, mentor and hire engineers, review designs, and drive reliability, observability, CI/CD, cost, latency, and production ML excellence across Python, Rust, Spark, AWS, Kubernetes, and model-serving infrastructure.

Conduct Android malware research, reverse engineering, and static and dynamic analysis. Detect emerging threats and attack vectors, analyze applications for malicious behavior, write detection rules, develop automation, and document findings for threat intelligence reports. Collaborate across teams and share technical knowledge. Requires at least three years of relevant research, reverse engineering, or low-level development experience, programming proficiency, and familiarity with malware analysis tools.

Research and analyze fraud detection mechanisms, abuse vectors, platform vulnerabilities, and emerging fraud tactics across web, mobile, social, forum, and dark web environments. Conduct OSINT and WEBINT investigations, validate abuse scenarios, operate technical research infrastructure, analyze datasets and telemetry, automate workflows, monitor third-party channels, and deliver actionable intelligence and mitigation recommendations.

Investigate fraud methods and vulnerabilities across web, mobile, social media, forums, apps, and darknet platforms. Analyze intelligence sources and large datasets to identify malicious activity, behavioral vulnerabilities, and process bypasses. Monitor third-party channels, conduct OSINT investigations, and produce reports with actionable mitigation recommendations. The role may also support red-team exercises, automation, and scripting to uncover abuse methods.

Lead a multidisciplinary red teaming team to design and run adversarial tests, evaluate model risks, produce high-quality deliverables, and communicate findings to clients while improving methodologies and workflows.