Responsibilities:
- Understand organization vision, goals, and strategies; align priorities and pursue initiatives based on strategic fit.
- Drive Generative AI vision, strategy, and architecture for Content Supply Chain.
- Provide technical leadership and guidance to Generative AI and Content Supply Chain teams.
- Architect, design, and implement systems using Adobe tools to manage the content lifecycle (intake, planning, production, review, distribution).
- Architect and deliver a container-based approach to enable scalable app hosting.
- Design, implement, and maintain CI/CD pipelines for GenAI solutions.
- Define and deliver quality API access to multiple GenAI services.
- Collaborate with stakeholders to streamline solution change management.
- Monitor, optimize, and troubleshoot production systems for high performance.
- Identify opportunities to optimize tasks using AI-driven solutions.
- Collaborate with data scientists, engineers, and designers to develop AI-powered tools and insights.
- Recruit, mentor, and coach team members; foster continuous learning and improvement.
- Promote Content Supply Chain/GenAI best practices through knowledge sharing and training.
- Communicate GenAI architecture strategies and initiatives to business stakeholders and leadership.
- Promote GenAI and DevOps value across Commercial and BTS organizations.
Tools/skills:
- Jira/Confluence; Azure OpenAI; Python; AWS EMR and Snowflake; Adobe Workfront and Adobe Experience Cloud.
Qualifications:
Required:
- Bachelorโs (7 years), Masterโs (6 years), or PhD (2 years).
- Proven Enterprise/Solution Architect experience focused on Content Supply Chain, AI/ML, and Generative AI.
- Strong understanding of generative AI techniques (e.g., deep generative models, autoregressive models, reinforcement learning).
- Knowledge of Sales/Marketing ecosystem and content lifecycle (creation, review, distribution).
- Hands-on ML experience (R/Python; applied math; deep learning frameworks/libraries).
- Expertise with LLMs (Azure OpenAI/ChatGPT 4.0 and other models) including GenAI API access.
- Expertise designing/managing CI/CD pipelines for GenAI; experience with LLM Ops.
- Understanding of AI agents (worker and orchestrator).
- Proven Python development and troubleshooting.
- Strong knowledge of containerization and orchestration; cloud platforms (AWS/Azure) and infrastructure as code.
- Multi-year AI/ML experience and exceptional communication/collaboration.