GuidePoint Security
AI/MLSecurityEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“AI/ML Security Engineer at GuidePoint Security. Skills: Agentic systems, AI/ML engineering, LLM integration, Prompt engineering. Design agentic harnesses. Build agentic harnesses”
What You'll Achieve.
Improve efficiency across service delivery; Improve efficiency across operations; Improve efficiency across sales functions; Build lasting agentic capability
Industry & Context.
Troubleshooting AI systems
Up to 10% travel, Sedentary work, Substantial hand movement, Close visual acuity
What They're Looking For.
Must Have
3+ years software development, 3+ years AI/ML engineering, Design, author, deploy agentic harnesses, Working knowledge Python, Working understanding LLMs, Prompt engineering knowledge, API-based AI integration knowledge, Independently scope, build, ship solutions, Explain technical concepts non-technical audiences
Nice to Have
Cloud platforms experience, Vector databases experience, Orchestration layers experience, Workflow automation platforms experience, Retrieval-augmented generation patterns, Tool-use/function-calling with LLMs, AI systems evaluation frameworks, AI systems benchmarks design, Technical enablement programs design, Technical enablement programs facilitation
What You'll Do.
Design agentic harnesses
Build agentic harnesses
Deploy agentic harnesses
Design LLM-integrated workflows
Build LLM-integrated workflows
Deploy LLM-integrated workflows
Define performance benchmarks
Own performance benchmarks
Evaluate emerging AI tools
Recommend emerging AI tools
Evaluate emerging AI models
Recommend emerging AI models
Evaluate emerging AI platforms
Recommend emerging AI platforms
Identify AI-powered automations
Develop AI-powered automations
Maintain AI-powered automations
Lead workflow assessments
Design repeatable frameworks
Design scalable frameworks
Own iteration on productized AI
Own iteration on proof-of-concept builds
Design enablement programs
Deliver enablement programs
Develop training materials
How You'll Work.
Team & Collaboration
Regional teams capability; Functional teams capability
Communication Scope
Explain technical concepts
Process & Methodology
Full delivery lifecycle
Full Job Description
GuidePoint Security provides trusted cybersecurity expertise, solutions and services that help organizations make better decisions and minimize risk. By taking a three-tiered, holistic approach for evaluating security posture and ecosystems, GuidePoint enables some of the nation’s top organizations, such as Fortune 500 companies and U. S. government agencies, to identify threats, optimize resources and integrate best-fit solutions that mitigate risk. General Description GuidePoint Security is seeking an Applied AI Engineer to join our AI and Agentic Enablement practice. This is a mid-level engineering role for practitioners with hands-on experience designing and deploying agentic systems. The role spans harness development within existing agentic platforms, internal tooling for NE regional teams, and structured enablement programs that build lasting agentic capability across the organization. Working independently across the full delivery lifecycle, this engineer leads harness design and deployment, owns internal tooling initiatives, and drives the enablement programs that transfer agentic operating capability to regional teams. Roles and Responsibilities: Design, build, and deploy agentic harnesses and LLM-integrated workflows from prototype through production within existing platforms Define and own performance benchmarks to evaluate reliability, accuracy, and continuous improvement of agentic pipelines Evaluate and recommend emerging AI tools, models, and platforms for adoption Identify, develop, and maintain AI-powered automations and tools that improve efficiency across service delivery, operations, and sales functions throughout the Northeast region Lead workflow assessments to identify opportunities for agentic automation and design repeatable, scalable delivery frameworks Own documentation, testing, and iteration on productized AI components and proof-of-concept builds for internal and client audiences Design and deliver enablement programs that build region
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