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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 (VIBESEC).
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 a Infrastructure Tech Lead.
What You'll Do:
Ship features across the stack, back end and front end, in your first months to learn the product, the codebase and the teams
Lead architectural and infrastructure initiatives end to end, from design to production: modernizing our mature PHP monolith, into microservices architecture, converting background processing to (TypeScript/Python) serverless on AWS, improving observability, and scaling our analytics on ClickHouse
Make key technical decisions and set best practices: system design, data models, code quality and testing, and when to bring in new technologies
Shape our agentic SDLC: how we plan, build, review and test with AI coding agents, and the guardrails around it
Write and review critical code across the stack, front end included, and mentor engineers through design and code reviews
Share ownership of production, including the on-call rotation
Work closely with Product, team leads and engineers across R&D to turn business needs into sound technical plans

We are looking for an Escalation Engineer (part of the Engineering organization) to support escalation points from both the Customer Success organization as well as internally within the engineering teams. This position may also include interfacing with customers.

Responsibilities:
Troubleshoot, debug, analyze logs, profile code & provide temporary or permanent solutions.
Work closely with engineering teams to propose fixes or temporary workarounds for critical customer issues.
Build supporting automation to improve productivity (of both yourself and the team).
Understand customer use cases and work closely with Customer Success Engineers and Solution Architects to be an effective channel between Engineering teams and Customer Success.
Take complete ownership and follow-up on escalations.
Collaborate cross-functionally to solve difficult technical problems.

Alice is a leading platform for Trust & Safety teams worldwide, combining cutting-edge AI with world-class expertise to protect users from the widest spectrum of online harms and keep customers two steps ahead of bad actors. We are looking for a Senior GenAI Data Scientist with strong hands-on experience in GenAI red teaming, adversarial testing, machine learning, and large-scale data analysis. You will develop the data science and ML capabilities behind an automated GenAI red-teaming platform. You will analyze and cluster adversarial prompts, identify emerging attack patterns, build models for automated prompt generation and mutation, and develop data-driven methods for prioritizing and evaluating security risks across different AI models. We are looking for a hands-on technologist with deep expertise in data science: clustering, scaling, machine learning, and statistical analysis. Key Responsibilities
* Build agents that act as data scientists at scale, reasoning, planning, and executing multi-step workflows to generate and analyze adversarial attacks.
* Manage and analyze prompt and response data from multiple sources (red-team campaigns, model evaluations, synthetic attacks); clean, curate, normalize, and label it for analysis.
* Analyze large volumes of structured and unstructured data to uncover trends, clusters, and anomalies, such as attack families, jailbreak techniques, and previously unseen patterns.
* Develop ML models and predictive algorithms to automate red-teaming.
* Build evaluation and monitoring pipelines to measure attack success and track model behavior across models and providers.
* Use statistical techniques and experiments to validate findings and ensure accuracy and reproducibility.
* Take research to production: build reliable, scalable systems optimized for cost and latency, with solid engineering practices (testing, CI/CD, telemetry).


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're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences.
If you've built agents that actually made it to production - and you care as much about evaluation, guardrails, and reliability as you do about capability - we want to talk to you.
Responsibilities
Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills.
Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail.
Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot.
Optimize agents for latency, cost, and reliability at enterprise scale.
Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Partner closely with product, data, and platform teams to translate customer needs into agent capabilities.

We're looking for a smart and capable DevOps Engineer. You will be part of a small and agile team, working on well-built infrastructure, handling production workloads, building and maintaining infrastructure that supports continuous delivery. This job includes work across the devops stack, including agent development, CI/CD, networking, resource allocation, cloud architecture, security, developer experience, and more.
We work with enterprise customers, with the SLA and expectations that this dictates.
This position includes on-call shifts.
Our stack:
Kubernetes on AWS
Terraform and IAC
Github & Github Actions
Responsibilities
What will you DO:
Design and evolve our cloud multi-region architecture on AWS - networking, interconnects, IAM and high-availability topology - and express it entirely as code with Terraform, following GitOps as a first principle.
Build and own the CI/CD pipelines that plan, review, test and safely apply IaC changes - Policy-as-Code guardrails, drift detection and progressive rollout so infrastructure changes ship as confidently as application code.
Advance Platform-as-a-Product: build self-serve capabilities and paved paths so engineers can provision what they need
Strengthen our observability stack - metrics, logs, traces and alerting.
Troubleshoot and mitigate production incidents, participating in on-call rotations to ensure system health and stability.
Design and develop the next generation of AI agents to support higher pace and evolve the RnD productivity while maintaining security and engage the entire company to use AI for better solutions.

We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership.
As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level.
You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers.
Responsibilities
Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies.
Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents.
Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph.
System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows.
Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop.
Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks.
Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment.