Design Advanced AI Solutions: Develop and implement generative AI systems using patterns such as retrieval-augmented generation, multi-agent orchestration, and GraphRAG; select large language models considering cost, latency, and accuracy. Embed Security from Inception: Utilize security scanning tools for real-time code analysis and enforce data flow protocols per classification requirements; promote “Governance as Guardrails” to integrate compliance and security throughout development. Lead Full-Stack Development: Execute development across the technology stack, including data pipelines, API integrations, and front-end interfaces (using Python and C#); build reusable libraries to improve efficiency. Multiply Team Impact: Conduct code reviews, lead architecture design sessions, and mentor U.S. and GDC teams in agent-oriented programming and advanced prompt engineering. Own AI CI/CD (LLMOps): Define and implement AI-specific CI/CD pipelines, ensuring monitoring for model performance drift and hallucination detection; streamline deployment to cloud environments. Align Technical and Business Goals: Collaborate with product owners, data scientists, and cybersecurity professionals to ensure solutions are secure, technically sound, and aligned with business objectives. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or related discipline; equivalent industry experience considered. Minimum of five years in software or system engineering, including experience delivering AI/ML solutions in production environments. Advanced proficiency in Python and experience with generative AI orchestration frameworks; expertise in vector databases and familiarity with cloud AI services (Azure OpenAI, AWS Bedrock). Practical experience with DevSecOps for AI systems, including model vulnerability scanning and secure data management; familiarity with code scanning and vulnerability management tools. Demonstrated ability to design and deploy AI solutions at production scale. Proven leadership and mentoring experience within technical teams or communities. Experience with multi-agent system design or advanced RAG architectures. Contributions to open-source AI frameworks or publications in AI research. Ability to communicate complex technical concepts effectively to non-technical audiences.
