Sr. Manager, AI & Process Improvement - Global

Deckers International HK Limited; Hong Kong; On-site; HKD 1,200,000 - 2,100,000; Full time

Job summary

Deckers International HK Limited seeks a Sr. Manager, AI & Process Improvement - Global to lead a growing AI team.

You will design, build, and deploy enterprise-scale AI and generative AI solutions across Supply Chain COE functions including shipping, planning, RFID enablement, and inventory handoff to stores and partners. You will mentor engineers, partner with data scientists and product teams, and drive measurable business value with scalable AI platforms.

Qualifications

• 10–12+ years in Software Engineering, AI, or tech-led process transformation.
• 3+ years working with Generative AI and LLMs.
• Experience building production AI systems and scalable architectures.
• Experience deploying AI applications on cloud platforms.
• Experience with vector and SQL databases, REST APIs and microservices.
• Experience with containerized deployments.

Responsibilities

• Lead AI architecture and solutions for supply chain COE functions (25%).
• Develop Generative and Agentic AI solutions and deploy workflows across vendors, DCs, and partners (20%).
• Provide AI analytics support, connecting APIs and BI tools for decision making (15%).
• Lead people development, define AI operating model, and mentor team members (20%).
• Scale AI platform with reusable microservices, orchestration, and monitoring (20%).

Skills

AI & ML

LLMs

Prompt Engineering

Agentic AI

Vector Databases

Cloud Platforms

Data Processing

AI Frameworks

Architecture thinking

Leadership

Education

Bachelor's in CS/AI/DS/ML

Master's in CS/AI/DS/ML

Tools

LangChain

LangGraph

LlamaIndex

DSPy

Job description

Sr. Manager, AI & Process Improvement - Global

We are looking for a highly skilled AI Engineering Leader / AI Architect to lead a growing team and design, develop, and deploy enterprise-scale Artificial Intelligence and Generative AI solutions across Supply Chain COE functions, including shipping, planning, RFID enablement, packaging, transportation, warehousing, and inventory handoff processes. The ideal candidate will combine deep technical expertise in Large Language Models, Agentic AI, Retrieval-Augmented Generation, AI system architecture, APIs, EDIs, FastAPI, cloud deployment, multi-agent workflows, MLOps, and AI governance with strong people leadership, team development, stakeholder management, and delivery accountability.

You will lead and develop direct reports while collaborating with data scientists, software engineers, product teams, and business stakeholders to build scalable AI solutions and platforms that solve real-world supply chain problems from vendor shipping, warehousing, and transportation through DC inventory handoff to stores, e-commerce customers, and wholesale partners.

Essential Functions & Responsibilities

Lead AI architecture and solutions for supply chain COE functions (25%):

• Develop AI solutions for repetitive tasks in shipping, customs clearance, planning, transportation, broker ops, manufacturing and vendor management and vendor communications
• Prioritize initiatives that improve control, speed, accuracy, and scalability across enterprise workflow
• Translate business needs into executable plans, automation stages and create OKR milestones, and measurable outcomes through biweekly sprints.
• Design end-to-end AI/ ML and generative or agentic solutions for existing tasks that improvement and stability
• Develop scalable, stable, secure and connected AI solutions for COE processes
• Select appropriate models, framework & reusable tools for each type of problem
• Stay constantly in touch with D&D team for access and tech upgrades

Generative and Agentic AI Development and Deployment (20%):

• Build Retrieval-Augmented Generation (RAG) pipelines. Use Monday.com or other platforms to track projects and deployments
• Develop Agentic AI workflows using multi-agent frameworks to connect manufacturing vendors, freight forwarders, DCs and other external platform to internal systems
• Evaluate and benchmark LLM performance and help with analytics and decision making

AI Analytics and Data support (15%)

• Develop scalable inference pipelines for APIs and connected agents
• Connect reporting and decision-making tools for our dashboards and control towers; Weekly summarized reports for execs
• Implement vector search and semantic retrieval of data form various sources to build end to end cost models and other optimization models for better packaging, solutions for manufacturing vendors
• Interact with Tableau and other BI tools to bring AI driven decision making and executive recommendations including risk tracking W-o-W
• Be an expert in processing PDFs, images, unstructured data, metadata extraction and indexing.

People leadership, team development, and AI operating model management (20%):

• Lead an initial team of 3 direct reports, including AI engineers, process improvement resources, and process owners, with accountability for priorities, workload planning, coaching, performance expectations, and delivery quality.
• Serve as the AI mentor and technical leadership anchor for the Supply Chain COE team, building engineering capability, improving solution design discipline, and helping team members grow into broader AI, automation, and process transformation responsibilities.
• Conduct architecture reviews, biweekly training sessions, build AI success stories and also be able to analyze cost benefits for every AI process improved
• Define coding standards and AI best practices, help improve the prompts used by the team to build AI agents.
• Collaborate frequently and methodically with product, supply chain, finance, technology, security, and operations teams to align priorities, manage trade-offs, remove blockers, and ensure the AI roadmap delivers measurable business value.

Scaling AI platform for future use (20%):

• Build reusable AI microservices and agents; One model helps solve another
• Develop orchestration workflows with multiple agents
• Integrate AI applications with enterprise systems like Tableau and Power BI
• Implement monitoring, logging, and observability. Deploy AI models using Docker and Kubernetes.
• Build a continuous improvement pipeline for AI applications.
• Track AI adoption for hours saved, resources trained and adopted, models built etc. through tangible weekly KPIs

Required Skills

• AI & Machine Learning: Machine Learning fundamentals, Deep Learning, Transformers, LLMs, AI Prompt Engineering, Fine-tuning, Embeddings, RAG, Agentic AI, Function Calling
• AI Frameworks: LangChain, LangGraph, LlamaIndex, DSPy (good to have)
• Vector Databases: Pinecone, Chroma DB, Tableau, Power BI, SQL DB, Oracle
• Cloud: Azure, Google Cloud Platform, AWS
• Data Processing: Pandas, Spark (preferred), Airflow (preferred)

Required Experience

• 10–12+ years in Software Engineering, AI, Machine Learning, or technology-led process transformation, including experience leading technical teams or directly managing engineers, analysts, or process improvement resources.
• 3+ years working with Generative AI and LLMs.
• Experience building production AI systems, designing scalable AI architectures.
• Experience deploying AI applications on cloud platforms.
• Experience with vector and SQL databases, REST APIs and microservices.
• Experience with containerized deployments.

Preferred Qualifications

• Experience with Graph RAG, Tableau, Knowledge Graphs.
• Experience with multimodal AI (text, image, audio, video).
• Experience building AI agents and autonomous workflows inside & outside Co-pilot
• Familiarity with model evaluation frameworks, predictive analytics,
• Experience with manufacturing processes, supply chain processes, data simulation and optimization tools.
• Understanding of AI governance, responsible AI, and Deckers data security policies.

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management.
• Lead with empathy, accountability, and a results-focused mindset; develop and mentor direct reports, build trust across teams, set clear expectations, and create an environment where team members can take on larger AI, automation, and process transformation challenges.
• Ability to translate business problems into AI solutions. Good listener
• Strong architectural thinking, along with business acumen
• Mentoring and leadership experience.
• Ownership and accountability.
• Ability to work in cross-functional teams.
• Project management and change management skills

Education

Bachelor’s or master’s degree in computer science, Artificial Intelligence, Data Science, Machine Learning, or a related field.

Metrics

• Deliver scalable, production-ready AI solutions across Supply Chain COE org
• Achieve low-latency, high-throughput AI inference with manufacturing product, packaging and services vendors
• Build, mentor, and scale a high-performing AI and process improvement team that can deliver reusable AI agents, automation solutions, adoption playbooks, and measurable productivity gains across the Supply Chain COE.
• Drive innovation in enterprise AI architecture and platform solutions capabilities.