AI Engineer

• Own the full lifecycle of AI-powered applications, including requirements definition, architecture, development, deployment, and ongoing evolution.
• Design and develop modern, performant web applications using React, with a focus on usability, accessibility, and clarity of experience.
• Build and maintain backend services using Python (Flask required), ensuring scalable, well-structured API design.
• Develop AI-native application features, including RAG-based workflows, conversational interfaces, and intelligent document generation.
• Design and implement event-driven, agentic workflows that respond to real-world signals (e.g., emails, meetings, documents) and trigger appropriate system actions or user prompts.
• Build systems that extract structured insights from unstructured data sources (natural language, documents, communications) to support downstream workflows and decision-making.
• Integrate AI/LLM services (e.g., OpenAI, Anthropic) into production systems with attention to performance, cost, and reliability.
• Collaborate with data developers and knowledge experts to translate pipelines and machine learning outputs into user-facing capabilities.
• Partner directly with stakeholders across the firm to define problems, prototype solutions, and iteratively deliver meaningful outcomes.
• Contribute to the development of shared platform capabilities, including component libraries, authentication patterns, and developer tooling.
• Implement and maintain CI/CD pipelines, containerized deployments, and cloud infrastructure (Azure preferred).
• Ensure all applications align with HED governance standards, including security, authentication, observability, and responsible AI practices.
• Monitor application health, troubleshoot production issues, and maintain clear documentation and operational runbooks.
• Actively contribute to a culture of innovation, experimentation, and continuous improvement across the Data & AI Platform team.
• Participate in structured technical reviews and cross-functional governance processes; contribute to architecture decision records (ADRs), operational runbooks, and review artifacts.
• Champion production-grade engineering practices including API versioning, error handling, automated testing, and scalability patterns.

AI Application Developer