Senior Cloud Security Automation & AI Engineer at GuidePoint Security

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 We are looking for a skilled Senior Cloud Security Automation & AI Engineer to support the Cloud Security Automation and AI Practice. This role combines hands-on delivery, technical oversight, presales support, and practice development to help organizations adopt and secure AI/ML platforms across multi-cloud environments. The Senior Cloud Security Automation & AI Engineer will be required to demonstrate strong technical depth across cloud-native AI services, agentic AI design patterns, and AI governance frameworks. This individual will compose and secure agentic AI solutions, implement AI gateways and policy-based controls, and translate complex security and automation requirements into actionable, outcome-driven solutions. They will lead by influence and bring business acumen to drive the adoption of progressive cloud security automation programs aligned with client objectives and practice priorities. About the Cloud Security Automation and AI Practice The Cloud Security Automation and AI Practice is responsible for helping organizations securely adopt, deploy, and govern AI/ML workloads and automation pipelines across cloud environments. We deliver advisory, implementation, and managed services that bridge the gap between innovation and security. Our team of engineers, architects, and consultants focuses on cloud-native AI platforms, security automation frameworks, and enterprise AI governance. We partner with clients, account executives, and technology vendors to deliver solutions that reduce risk while accelerating AI adoption. Deliver secure AI/ML platform implementations across AWS, Azure, Google Cloud, and third-party enterprise AI platforms Develop reusable automation frameworks, accelerators, and reference architectures for AI security Drive thought leadership and practice growth through presales support, content development, and industry engagement Roles and Responsibilities Delivery & Technical Execution Lead end-to-end delivery of cloud security automation and AI engagements, including scoping, architecture design, implementation, and client handoff Design and implement secure agentic AI solutions, including multi-agent orchestration, Model Context Protocol (MCP) integrations, AI gateway architectures, and policy-based access controls using frameworks such as Cedar Architect and enforce AI governance policies, including usage policies, data handling controls, model access management, and compliance guardrails for enterprise AI deployments Develop and deploy AI-powered security automation solutions (e.g., automated compliance checks, threat detection agents, remediation workflows) for clients Produce high-quality deliverables including architecture documents, runbooks, SOPs, and security assessment reports Technical Oversight & Quality Assurance Provide technical oversight and quality assurance across active engagements, ensuring deliverables meet GuidePoint standards and client expectations Mentor and guide junior engineers on best practices for cloud security, AI/ML implementation, and secure development Conduct architecture reviews, code reviews, and security assessments for AI/ML workloads Presales & Business Development Support Support presales activities by participating in client discovery calls, demos, and technical deep dives Contribute to proposals, statements of work (SOWs), and pricing estimates for AI security and automation engagements Collaborate with account executives and practice leadership to identify opportunities and shape client solutions Practice Development & Thought Leadership Contribute to practice development by building reusable tools, templates, accelerators, and reference architectures Develop thought leadership content such as blog posts, whitepapers, webinars, and conference presentations Stay current on emerging AI/ML platforms, cloud security trends, and regulatory developments to inform practice strategy Required Experience and Education Bachelor's Degree (BS/BA) + 5-7 years of experience Demonstrated experience designing, implementing, or securing AI/ML workloads in cloud environments Hands-on proficiency with primary AI/ML platforms: Amazon Bedrock, Amazon Q, and Amazon SageMaker Preferred experience with secondary platforms: Azure AI Foundry, Microsoft 365 Copilot, Copilot Studio, Azure Machine Learning Experience in a client-facing consulting or professional services role Embraces emerging technologies, including AI tools, to work smarter, solve problems, and drive better business outcomes Basic Python competency, including the ability to read, write, and troubleshoot code for automation and integration tasks Understanding of agentic AI patterns, AI governance frameworks, and secure AI composition (e.g., multi-agent orchestration, tool-use guardrails, prompt injection mitigation) Technology Proficiency Primary (AWS) Amazon Bedrock Amazon Q (Business, Developer) Amazon SageMaker Secondary (Azure) Azure AI Foundry Microsoft 365 Copilot Copilot Studio Azure Machine Learning Additional Platforms Gemini for Google Workspace Claude for Enterprise (Anthropic) ChatGPT Enterprise / OpenAI Platform AI Security & Governance AI Gateways (centralized proxy, traffic control, policy enforcement) Model Context Protocol (MCP) Cedar (AWS policy language for fine-grained authorization) AI governance and usage policy frameworks (NIST AI RMF, ISO 42001, OWASP LLM Top 10) Preferred Experience and Education AWS Certified Solutions Architect, AWS Certified Machine Learning, or AWS AI Practitioner certification Azure AI Engineer Associate, Azure Solutions Architect Expert, or Microsoft 365 Certified: Administrator Expert Google Cloud Professional Machine Learning Engineer or Google Cloud Professional Cloud Architect Experience writing statements of work (SOWs), proposals, or scoping documents for professional services engagements Background in security frameworks (NIST AI RMF, OWASP LLM Top 10, ISO 42001) as applied to AI/ML workloads Public speaking experience, including presentations at conferences, webinars, or industry events Prior experience in practice development, service catalog creation, or go-to-market strategy for a consulting or professional services firm AWS Certified Developer - Associate Experience with AI gateways, Model Context Protocol (MCP), and policy-as-code frameworks (e.g., Cedar, OPA) Travel Requirements Up to 20% travel Physical Requirements Sedentary work Substantial movement of the wrists, hands, and/or fingers for a minimum of 8 hours a day Required to have close visual acuity to view computer terminal and/or extensive reading for a minimum of 8 hours a day We use Greenhouse Software as our applicant tracking system and Zoom Scheduler for HR screen request scheduling. At times, your email may block our communication with you. Please be sure to check your SPAM folder so that you don't miss updates on your application. Why GuidePoint? GuidePoint Security is a rapidly growing, profitable, privately-held value added reseller that focuses exclusively on Information Security. Since its inception in 2011, GuidePoint has grown to over 1,300 employees, established strategic partnerships with leading security vendors, and serves as a trusted advisor to more than 6,200 customers. Firmly-defined core values drive all aspects of the business, which have been paramount to the company’s success and establishment of an enjoyable workplace atmosphere. At GuidePoint, your colleagues are knowledgeable, skilled, and experienced and will seek to collaborate and provide mentorship and guidance at every opportunity. This is a unique and rare opportunity to grow your career along with one of the fastest growing companies in the nation. Some added perks…. Remote workforce primarily (U.S. based only, some travel may be required for certain positions, working on-site may be required for Federal positions) Group Medical Insurance options: Zero Deductible PPO Plan (GuidePoint pays 90% of the premium for employees and 70% for family plans (spouse/children/family) or High Deductible Health Plan with HSA (GuidePoint pays 100% of the employees premiums and 75% for family plans (spouse/children/family). If you choose the High Deductible / HSA plan, GPS will contribute in 4 equal quarterly installments: ($850 per EE annually / $1750 per family annually (includes spouse/children/family options) Group Dental Insurance: GuidePoint pays 100% of the premium for employees and 75% of family plans 12 corporate holidays and a Flexible Time Off (FTO) program Healthy mobile phone and home internet allowance Eligibility for retirement plan after 2 months at open enrollment Pet Benefit Option

Requirements

Must-haves

About the Cloud Security Automation and AI Practice
Deliver secure AI/ML platform implementations across AWS, Azure, Google Cloud, and third-party enterprise AI platforms
Develop reusable automation frameworks, accelerators, and reference architectures for AI security
Drive thought leadership and practice growth through presales support, content development, and industry engagement
Roles and Responsibilities
Delivery & Technical Execution
Lead end-to-end delivery of cloud security automation and AI engagements, including scoping, architecture design, implementation, and client handoff
Design and implement secure agentic AI solutions, including multi-agent orchestration, Model Context Protocol (MCP) integrations, AI gateway architectures, and policy-based access controls using frameworks such as Cedar
Architect and enforce AI governance policies, including usage policies, data handling controls, model access management, and compliance guardrails for enterprise AI deployments
Develop and deploy AI-powered security automation solutions (e.g., automated compliance checks, threat detection agents, remediation workflows) for clients
Produce high-quality deliverables including architecture documents, runbooks, SOPs, and security assessment reports
Technical Oversight & Quality Assurance
Provide technical oversight and quality assurance across active engagements, ensuring deliverables meet GuidePoint standards and client expectations
Mentor and guide junior engineers on best practices for cloud security, AI/ML implementation, and secure development
Conduct architecture reviews, code reviews, and security assessments for AI/ML workloads
Presales & Business Development Support
Support presales activities by participating in client discovery calls, demos, and technical deep dives
Contribute to proposals, statements of work (SOWs), and pricing estimates for AI security and automation engagements
Collaborate with account executives and practice leadership to identify opportunities and shape client solutions
Practice Development & Thought Leadership
Contribute to practice development by building reusable tools, templates, accelerators, and reference architectures
Develop thought leadership content such as blog posts, whitepapers, webinars, and conference presentations

Nice-to-haves

Preferred experience with secondary platforms: Azure AI Foundry, Microsoft 365 Copilot, Copilot Studio, Azure Machine Learning
Preferred Experience and Education

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Benefits

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Dental