Innovation Engineer- Remote (Anywhere in the U.S.)

GuidePoint Security is seeking a skilled and security-conscious Innovation Engineer to join our technology team. This role is pivotal in building and scaling our generative AI capabilities. You will be responsible for the design, implementation, security, and operational management of generative AI solutions that will be leveraged internally. You will work closely with IT infrastructure and information security teams to ensure all implementations adhere to enterprise security standards, company policies, and industry best practices. This role offers the exciting opportunity to contribute to our AI strategy and potentially expand into more advanced ML implementations as the program and capabilities mature. The Innovation Engineer will be required to demonstrate patience, self-motivation, and strong business/financial acumen.

Responsibilities

Design & Implement GenAI Solutions; Enable Technical Users; Data Integration; Security & Compliance; Operational Excellence; Collaboration; Stay Current; Documentation; Future Planning; Facilitate Education

Requirements

5+ years of experience in cloud engineering and/or solutions architecture with a significant focus on AWS; Deep hands-on experience implementing, managing, and supporting AI solutions using AWS services within an enterprise context; Strong understanding and practical experience with core AWS services (e.g., IAM, DynamoDB, S3, Lambda, CloudWatch, CloudTrail); Proven experience designing and implementing secure, cloud-based AI solutions on AWS, including familiarity with AWS security services (e.g., Guardrails, KMS, Secrets Manager); Enterprise-level experience with AI-focused AWS services such as Bedrock, SageMaker, Transcribe, Rekognition, and Q Business; Demonstrated experience working collaboratively with IT Operations and Information Security teams on cloud deployments and security reviews; Proficiency in at least one relevant programming language, preferably Python; Solid understanding of generative AI concepts, Large Language Models (LLMs), prompt engineering, and foundational AI/ML principles; Excellent problem-solving skills and ability to troubleshoot complex technical issues; Strong written and oral communication and interpersonal skills; Demonstrated experience applying security principles to AI implementations; Understanding of AI-specific security challenges including prompt injection, data poisoning, and model extraction attacks; Patience, self-motivation, and strong business/financial acumen

Nice to have

AWS Certified Cloud Practitioner; AWS Certified AI Practitioner; AWS Certified Solutions Architect; AWS Certified Machine Learning Engineer; Understanding or experience with model fine-tuning techniques; Experience with Infrastructure as Code (IaC) tools like AWS CloudFormation, Terraform, OpenTofu, or equivalent technologies; Familiarity with MLOps principles and practices; Experience integrating AI services with enterprise applications and data warehouses; Experience designing and implementing agentic AI architectures that can autonomously perform complex workflows while maintaining appropriate security boundaries and human oversight; Familiarity with MCP client/server architecture and the associated security risks

Benefits

Remote workforce primarily (U.S. based only); Group Medical Insurance options; Group Dental Insurance; 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