Engineer, IT, AI Enablement

Design Advanced AI Solutions: Develop and implement generative AI systems applying contemporary patterns such as retrieval-augmented generation, multi-agent orchestration, and GraphRAG; select large language models with careful consideration of cost, latency, and accuracy. Embed Security from Inception: Employ security scanning tools for real-time code analysis and enforce data flow protocols in line with classification requirements. Promote a “Governance as Guardrails” methodology to integrate compliance and security throughout the development process. Lead Full-Stack Development: Complete development across the technology stack, including data pipelines, API integrations, and front-end interfaces (using languages such as Python and C#); construct reusable libraries to enhance development efficiency. Multiply Team Impact: Conduct comprehensive code reviews, lead architecture design sessions, and facilitate skill advancement for both U.S. and GDC teams in agent-oriented programming and advanced prompt engineering. Own AI CI/CD (LLMOps): Define and implement continuous integration and deployment pipelines specific to AI (LLMOps), ensuring robust monitoring (including model performance drift and hallucination detection) and streamlined deployment of AI solutions to cloud environments. Align Technical and Business Goals: Partner with product owners, data scientists, and cybersecurity professionals to ensure solutions are technically sound, secure, and aligned with business objectives.