AI Solutions Engineer
apple
Job Description
Responsibilities
- Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, anomaly/exception handling, data monitoring).
- Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools.
- Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains.
- Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads.
- Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk).
- Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance.
- Work closely with cross functional supply chain IT and operations teams to translate business challenges into AI-driven solutions.
- Bring functional understanding across areas like S&OP, inventory management, supplier risk, and procurement operations.
- Drive continuous improvement through digital twin models, predictive analytics, and scenario simulation.
- Collaborate with data scientists, and engineers in a fast-paced agile environment.
- Act as a thought leader in identifying high-value opportunities for AI within the enterprise supply chain.
- Present technical concepts and business value to executive stakeholders clearly and persuasively.
Minimum Qualifications
- Bachelor’s or Master’s in Computer Science, Data Science, Operations Research, or a related field.
- 7+ years of experience in data engineering, AI/ML, or analytics roles.
- 4+ years of hands-on experience with Generative AI (e.g., GPT, Claude, open-source LLMs) and Agent-based architectures (LangChain, AutoGen, etc.).
- Strong background in data science: SQL, Spark, Python, Airflow, cloud (AWS/GCP/Azure), and data lakes.
- Deep understanding of supply chain processes (planning, logistics, procurement, manufacturing).
- Familiarity with MLOps tools, vector databases (e.g., Pinecone, FAISS), and AI safety practices.
Preferred Qualifications
- Experience with commercial supply chain platforms (e.g., Kinaxis, Blue Yonder).
- Exposure to digital twin and simulation platforms.
- Strong storytelling, communication, and stakeholder management skills.
- Experience in collaborating with global teams in a matrixed organization.