AI Solutions Engineer

Responsibilities

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions addressing real-world challenges.
• Engage directly with customers to understand their business problems and assist in the implementation of generative AI solutions.
• Brief customers and guide them on adoption strategies and production deployment pathways.
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations tailored to technical, business, and executive audiences.
• Provide customer and market feedback to product and engineering teams to influence product direction and roadmap.
• Implement data pipelines, vectorization methods, and API integrations using Python.
• Contribute to existing AI-enabled full-stack web projects built in Python and React.
• Utilize AWS AI/ML services such as Amazon SageMaker, Bedrock, and Comprehend for model development, fine-tuning, and orchestration.
• Manage structured and unstructured data using AWS storage and retrieval solutions like Amazon S3, OpenSearch, and Aurora.
• Apply vector database technologies such as FAISS, Pinecone, or OpenSearch vector search for document retrieval and similarity search.
• Integrate LLM APIs and apply prompt engineering techniques to connect retrieval systems with generative models.
• Demonstrate basic DevOps and security awareness on AWS, including IAM roles, networking (VPCs), and data encryption practices.
• Use containerization and orchestration tools such as Docker and AWS Lambda/ECS for scalable RAG (Retrieval-Augmented Generation) pipeline deployment.
• Utilize AWS Lambda to run responses triggered by alerts from integrated services.
• Support security and operations using AWS-native technologies, ensuring compliance with DoD security requirements.
• Evaluate and propose new AWS technologies and modernization paths to enhance operational efficiency and security with AI solutions.
• Develop and maintain Standard Operating Procedures (SOPs), technical documentation, and reports on system operations.
• Adhere to Agile program best practices such as participation and management of team scrums and sprint plannings.
• Document and track all work using the program approved ticketing system.

  Qualifications

  • Strong technical expertise in AWS GovCloud and Microsoft Windows Server environments.
  • Excellent technical, organizational, decision-making, and analytical skills.
  • Strong Python experience including object-oriented development.
  • Experience with React or other frontend JavaScript web frameworks is a plus.
  • Strong communication skills with the ability to engage both technical staff and executive stakeholders.
  • Ability to enforce program best practices (ticketing, documentation, reporting).
  • Familiarity with DoD IT environments, compliance requirements, and cybersecurity standards.
  • Ability to adapt to a dynamic, fast-paced environment and support teams across geographically dispersed locations.
  • Bachelor’s degree in a STEM field from an accredited institution, or equivalent years of related work or military experience.
  • Minimum of 3 years of relevant professional experience, including systems administration and cloud operations.
  • Experience supporting DoD IT environments preferred.
  • Experience using Agile methodologies and ticketing systems such as JIRA is desirable.
  • Must have an active certification from the bullet list below: Active IAT II Certification which may include CompTIA Advanced Security Practitioner (CASP+), CompTIA Cybersecurity Analyst (CySA+), Certified Information Systems Security Professional (CISSP), or CompTIA Security+.
  • Must have AWS certification (e.g., AWS Certified AI Practitioner, AWS Certified Cloud Practitioner, AWS SysOps Administrator Associate, AWS Solutions Architect Associate).
  • Must currently have at least a Secret level security clearance in Hawaii and TS/SCI in Arlington, Virginia.
  • Must be a U.S. citizen.