Generative AI Solution Engineer

Summary

Join GuidePoint Security as a Generative AI Engineer/Architect and play a key role in building and scaling our generative AI capabilities. Design, implement, secure, and manage generative AI solutions leveraging both SaaS and local resources. Provide guidance and support to internal teams using SaaS AI services. Collaborate with IT infrastructure and information security teams to ensure compliance with enterprise security standards. Contribute to our AI strategy and potentially expand into more advanced ML implementations. This role requires strong business acumen and collaboration skills.

Requirements

• 5+ years of experience in cloud engineering and/or solutions architecture with a significant focus on AWS
• Deep hands-on experience specifically 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, the ability to troubleshoot complex technical issues, and the patience to come up with creative solutions that work for all stakeholders within policy boundaries
• Strong written and oral communication and interpersonal skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
• Demonstrated experience applying security principles to AI implementations, including data protection, access controls, and threat modeling for AI systems
• Understanding of AI-specific security challenges including prompt injection, data poisoning, and model extraction attacks

Responsibilities

• Design & Implement GenAI Solutions: Help design, build, deploy, and manage secure and scalable generative AI solutions using both SaaS and local resources
• Enable Technical Users: Provide guidance, best practices, and support to internal teams utilizing SaaS AI services to build custom applications
• Data Integration : Design and assist with implementing secure data connectors and ingestion pipelines to allow enterprise AI services to query internal organizational data sources (e.g., knowledge bases, document repositories)
• Security & Compliance : Collaborate closely with Information Security and IT teams to define security requirements, implement robust security controls (IAM policies, network configurations, data encryption, logging, monitoring), conduct security reviews, and ensure compliance with internal policies and relevant regulations for all AI deployments
• Operational Excellence : Assist as needed in establishing monitoring and alerting for applicable AI solutions and help develop operational procedures for deployed AI services. Optimize for performance, scalability, and cost-effectiveness
• Collaboration : Act as a liaison between business stakeholders, technical teams, IT operations, and information security regarding generative AI initiatives
• Stay Current : Keep abreast of the latest developments in SaaS AI/ML services, generative AI trends, and cloud security best practices
• Documentation : Create and maintain clear technical documentation, architecture diagrams, and security guidelines
• Future Planning : Contribute to the strategic roadmap for AI/ML within the organization
• Facilitate Education : Assist with maintaining, developing, and presenting educational material to internal users about effective and safe usage of AI

Preferred Qualifications

• 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, 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) and GPS will contribute in one lump sum: ($500 per EE annually / $1000 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