Lead GenAI Engineer

Consultant's Title: Lead GenAI Engineer

Work Location: San Francisco, CA (Bay Area preferred),

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.