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We are seeking an innovative AI Manager with an understanding of AI platforms, services, and tools for customer-facing teams. In this role, you will collaborate with Customer Success teams to identify business challenges, uncover growth opportunities, and leverage AI capabilities to bridge the gaps, drive team performance to achieve their KPIs. Key responsibilities include evaluating external AI solutions and collaborating with internal development teams to create custom tools tailored to our needs. Strong communication skills between business and technical teams are essential to ensure the right AI capabilities are matched to achieve desired business outcomes.
Collaborate with CS Team:
Work closely with Customer Success team leads to identify and analyze main pain points, challenges, and areas for improvement.
Conduct thorough assessments to understand team requirements, workflows and KPIs.
AI Solutions Strategy:
Develop and implement AI strategies to address identified pain points and develop new capabilities and insights.
Evaluate and recommend external AI vendors to meet specific needs.
Collaborate with internal dev teams to develop and integrate custom AI solutions.
Stay up-to-date with industry trends and advancements in AI technologies to continuously support the teams as the trusted AI Consultant.
Project Management:
Plan, design, and manage cross-functional projects E2E, ensuring successful delivery.
Oversee the implementation of AI projects, ensuring high quality, timely delivery and alignment with business goals.
Monitor project progress, address issues, and provide ongoing feedback and regular updates to stakeholders.
Additional Responsibilities:
Own CS business processes: drive process optimization, automation, and continuous improvement initiatives.
Translate business requirements into detailed design documents: user stories, solution specs, process diagrams, KPIs measurement & tracking, and reporting.
Build dashboards/reports to track key metrics and manage software that facilitates GTM activities.

were looking for an AI Product Specialist. In this individual-contributor role, you'll design and build production-ready AI agents, shape our prompt strategy, and ensure every customer-facing team can confidently demo and customize the Builder.

Youll spend approximately 60% of your time on hands-on agent building and prompt engineering, 30% on outbound enablement and GTM support, and 10% on special initiatives such as internal hackathons.

Responsibilities

Own the end-to-end design and development (mostly vibe-coding) of AI agents on our Builder platform, coordinating with stakeholders and ensuring clear, timely communication throughout the process.
Craft, test, and iterate prompts; establish reusable templates and guardrails to ensure the best user experience, trust, and consistent brand voice.
Collaborate closely with customer-facing teams to refine customer-tailored prompts and continuously improve product experience.
Identify new agent opportunities through market research, customer interviews, and field feedback; translate insights into a prioritized backlog.
Enable customer-facing teams (Solutions Engineering, CSM, Sales), Product, and Engineering teams with demo environments, playbooks, decks, and demo-in-a-box kits; run live enablement sessions and certification programs.
Track adoption KPIs of the AI Buildertraining completion, agent usageand present monthly scorecards to leadership.
Lead special initiatives, such as internal hackathons, to spark innovation and develop new production agents.
Serve as the primary subject-matter expert for advanced AI Builder questions, troubleshoot issues, and gather feedback for the product roadmap.

In this role, youll lead a team of top-tier software engineers, owning the architecture, scalability, and seamless integration of AI-driven capabilities into a high-performance, real-time security platform. You'll play a key role in transforming advanced AI technologies into impactful, production-ready solutions.

Our group combines the speed and creativity of a startup with the backing of a global cybersecurity leader. If you're passionate about solving complex technical problems, leading exceptional talent, and building innovative AI-powered systems with real-world impact we want to hear from you.


Key Responsibilities
Lead, mentor, and grow a team of software engineers, fostering a high-performing culture and supporting recruitment, onboarding, and career development
Drive the design, architecture, and technical direction of the AI-powered product, ensuring it meets performance, scalability, and integration goals
Work closely with data scientists, product managers, and engineering teams to align on strategy, execution, and delivery
Ensure robust, scalable, and reliable deployment in production
Stay on top of emerging AI technologies and best practices, evaluating and integrating advancements to keep the product and team at the cutting edge

We seek a Lead AI Engineer specializing in prompt engineering and optimizing large language models (LLMs) for real-world applications. In this role, you will not only design effective prompts, improve model responses, and build AI agents, but also take the lead in shaping and delivering the initial AI-powered product for the company. You'll be responsible for driving the technical vision, building from scratch, and leading the implementation of AI-driven capabilities that will become a core part of our product offering.
Responsibilities:
Prompt Engineering: Develop, test, and optimize prompts for high-quality AI responses across different tasks.
Retrieval-Augmented Generation (RAG): Implement RAG-based solutions to improve AI responses using external knowledge bases.
Integration & API Development: Work with software engineers to embed AI features into our product via APIs.
AI Agent Development: Design, build, and deploy autonomous AI agents that can reason, and execute multi-step tasks using LLMs, tools, memory, and APIs.
Experimentation & Evaluation: Continuously refine models using A/B testing, human feedback loops, and AI evaluation metrics.
Stay Updated: Keep up with the latest LLM advancements and best practices in the AI industry.
Product applications: Apply LLMs and agents to real-world scenarios that solve meaningful user problems.
Product implementation: Work closely with the product team to secure delivery is aligned with expected product requirements
Response validation: Implement a process to ensure accurate KPI measurement and consistent, expected outcomes.