Applied AI Manager

About the role:
Drive AI-native transformation across business and operational domains by identifying, implementing, and scaling GenAI productivity systems. This role blends deep process engineering expertise with hands-on AI fluency, translating frontier technologies into repeatable, cross-functional value.

What You'll Do:

• Lead AI-first process redesign initiatives across technical and non-technical domains (Care, Ops, Finance, HR, Product).
• Architect LLM-based productivity tools (e.g., copilots, retrieval-augmented assistants, AI action agents) tailored to team-specific workflows and enterprise data architecture.
• Translate unstructured processes into structured automations, via intelligent agents, prompt workflows, and API orchestration.
• Partner with AI and software engineers to develop custom pipelines leveraging open-source models, vector stores, and agent frameworks.
• Define success metrics and ROI for each AI use case; lead the change management, training, and adoption journeys.
• Establish scalable playbooks and frameworks to standardize AI deployment, monitor performance, and evolve solutions in response to usage patterns.

What You'll Need:

• 3-5 years of experience in transformation, process engineering, or operating model design—preferably in tech-forward or consulting environments.
• Track record of building or leading AI productivity tools or GenAI programs in complex, cross-functional settings.
• Proficiency in LLM stack architecture including model selection (proprietary vs. OSS), prompt chaining, vector DB integration, and multi-agent workflows.
• Systems thinker: able to map process bottlenecks to AI-powered augmentation, and define the delta between AI-enabled vs. AI-rewritten workflows.
• Strong builder/operator mindset; can drive from zero to one, then scale with robustness and observability.