Prompt Engineer

Vectra® is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises.

The Vectra AI Platform delivers integrated signal across public cloud, SaaS, identity, and data center networks in a single platform. Powered by patented Attack Signal Intelligence, it empowers security teams to rapidly prioritize, investigate and respond to the most advanced cyber-attacks. With 35 patents in AI-driven threat detection and the most vendor references in MITRE D3FEND, organizations worldwide rely on the Vectra AI to move at the speed and scale of hybrid attackers. For more information, visit www.vectra.ai. 

Vectra AI’s Office of the CTO is seeking to expand the Emerging Technologies team to include a Prompt Engineer contributing to the company’s next generation of AI-based products and services. This role will focus on ongoing research initiatives and prototypes centrally leveraging large language models (LLMs).

The ideal candidate will both collaborate through the difficult challenges of early-stage research and development while also working independently and autonomously in their specialized area of focus. Additionally, this role must be comfortable with the ambiguity of open-ended research while maintaining a strong bias to converge that research into a concrete and supportable specification and implementation.

Team Responsibilities:

• Envision, develop, and test prototypes to demonstrate feasibility and potential impact to new or existing lines of business.
• Transition prototypes from early-stage design into long-term supportable state in partnership and collaboration with peers across organizational boundaries.
• Research emerging or newly viable technologies to identify innovation opportunities.
• Promote continuous learning, experimentation, and collaboration throughout CTO organization and across organizational boundaries at Vectra AI.

Individual Responsibilities:

• Architect, build, and maintain infrastructure to support multi-agent LLM-based AI Assistants.
• Collaborate with security researchers, sales engineers, and UX teams to understand product use-cases and workflows, prototyping AI assistants and automation to achieve desired outcomes.
• Develop, test, and deploy machine learning models and AI algorithms, with a focus on large language models (LLMs).
• Optimize models for performance, scalability, and reliability.
• Design and implement data pipelines and workflows to support AI and ML projects.
• Educate the engineering organization on AI/LLM infrastructure and facilitate knowledge transfer to broader teams.
• Leverage AI/ML expertise to collaborate with cross-functional teams chartered to identify and enable opportunities for research acceleration through platform capabilities.
• Capacity to flex into adjacent technical domains to maintain research velocity.

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