Responsibilities:
- Architect and build a stateful, headless GenAI application for enterprise content creation and personalization.
- Design and implement multi-agent orchestration across AI agents, enterprise APIs, data services, and content repositories.
- Establish application architecture, technical standards, coding patterns, and API-first design principles.
- Develop robust services that generate structured JSON and HTML content blueprints for downstream applications.
- Implement conversational and project state management, multi-turn interactions, memory, and context retention.
- Build RAG and grounding capabilities to ensure generated content is supported by relevant enterprise information and source material.
- Develop streaming GenAI interfaces with clarification flows, conversation history, error handling, and resilient response management.
- Implement structured response rendering, including tables, charts, citations, and reusable results.
- Establish evaluation strategies and production observability to monitor quality, reliability, and application performance.
- Integrate GenAI capabilities with enterprise platforms, business systems, data services, and content repositories.
- Make key technical decisions, review other engineers' work, and establish scalable engineering practices.
- Write and deliver production-quality code while remaining actively involved in architecture and implementation.
Role with the Group (manager, programmer, etc.):
Senior hands-on technical lead responsible for GenAI application architecture, agentic orchestration, and implementation. This is an engineering role requiring direct coding and technical ownership, not a coordination-only or project-management position.
Required Skills:
- Significant hands-on experience architecting and building production-grade generative AI applications.
- Strong software engineering experience in Python or TypeScript.
- Experience designing and developing microservices and API-first architectures.
- Demonstrated experience with stateful, multi-turn GenAI applications and multi-agent orchestration.
- Strong understanding of structured contracts, API schemas, and machine-readable output formats.
- Experience building headless services that produce structured outputs for downstream applications.
- Experience integrating GenAI applications with enterprise platforms, data services, and content repositories.
- Practical experience with retrieval-augmented generation (RAG), grounding, application state, memory, and context management.
- Experience developing GenAI evaluation frameworks and production observability.
- Experience building streaming, multi-turn GenAI interfaces with clarification flows, conversation history, and error handling.
- Experience rendering structured responses, including tables, charts, citations, and reusable results.
- Ability to propose architecture, make technical decisions, establish coding patterns, review engineering work, and deliver production code.
- Strong AWS, Amazon Bedrock, and AgentCore experience.
Desired Skills:
- Experience with content generation, content-as-code, personalization, or marketing technology platforms.
- Experience with Workfront, Veeva Vault PromoMats, Adobe Experience Manager (AEM) Assets, or comparable enterprise content management systems.
- Experience working in commercial pharmaceutical or other regulated content environments.
- Experience designing systems that support enterprise content governance, source traceability, and reusable content components.