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Tier-1 brand and mid-level generalist title increase competition, though niche agentic AI requirements moderate the applicant pool.
Role demands specialized agentic AI, LLM productionization, and supply-chain context, limiting cross-industry transferability.
Multiple explicit years plus mandatory specialized agentic AI, MCP, RAG, vector DB, cloud, and Kubernetes requirements increase filtering strictness.
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Develop and productionize scalable, enterprise-grade AI applications powered by Generative AI, LLMs, AI agents, and RAG architectures.
Partner with business teams to understand workflows and identify high-impact AI automation opportunities within supply chain and enterprise operations.
Ensure AI solutions align with privacy, security, compliance, and responsible AI practices while creating reusable frameworks to accelerate AI development.
Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
3+ years experience working within or alongside supply chain or enterprise operations environments.
2+ years hands-on with agentic AI frameworks (e.g. LangGraph, Google Agent SDK) and MCP server development.
Experience building and deploying LLM-powered applications, REST APIs (preferably with FastAPI), and working knowledge of AI infrastructure including containerization (Docker, Kubernetes) and cloud deployment (AWS/GCP/Azure).
Experienced in building end-to-end AI solutions in supply chain or enterprise operational contexts with measurable business impact.
Comfortable operating in fast-paced, evolving environments requiring rapid prototyping and iteration of AI-driven automation.
Strong software engineering background with expertise in scalable backend systems, multi-agent orchestration, prompt engineering, and AI-native development workflows.