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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformNoSQLRedis
About the role
Key responsibilities & impact- Analyze supply chain processes across demand planning, supply planning, procurement, production planning, logistics, and inventory management.
- Translate business challenges into AI/agent-driven use cases, workflows, and decision frameworks.
- Define requirements, KPIs, data needs, and functional specifications for AI-enabled supply chain solutions.
- Validate AI/ML outputs—including forecasts, optimization recommendations, exception insights—and map them to business rules.
- Contribute to designing autonomous Agentic AI supply chain solutions, including agent roles, reasoning flows, and decision loops.
- Assist in building and validating AI agents using LLMs, RAG, prompt engineering, and domain knowledge modeling.
- Stay updated on latest advancements in LLMs, Generative AI, and agent-based architectures, assessing their applications in supply chain use cases.
- Integrate with APIs and libraries such as Azure OpenAI GPT models, Hugging Face Transformers, and other relevant frameworks.
- Support implementation and optimization of end-to-end AI pipelines (data → model → agent → workflow).
- Work with vector databases (e.g., Redis), NoSQL stores, and similarity search for knowledge retrieval and contextual decision-making within agents.
- Evaluate advanced AI techniques (transfer learning, domain adaptation, optimization algorithms) for supply-chain-specific tasks.
- Define evaluation metrics to measure the relevance, accuracy, and business impact of agent recommendations and outputs.
- Collaborate on data curation, cleaning, and preprocessing for AI and optimization models in supply chain contexts.
- Support MLOps practices around versioning, deployment, monitoring, and scaling of AI/LLM models.
- Participate in workshops, solution demos, PoV/PoC delivery, and client presentations.
Requirements
What you’ll need- Bachelor’s or Master’s degree in Supply Chain, Engineering, Operations, Computer Science, or related fields.
- 3–7 years of experience in supply domain Analytics
- Exposure to AI/ML, GenAI, LLMs, or digital supply chain transformation initiatives.
- Technical Skills Understanding of machine learning, NLP, or LLM-based techniques (GPT, Transformer models, BERT, etc.).
- Familiarity with optimization (MIP, linear programming) is preferred.
- Good exposure to cloud platforms (Azure, AWS, GCP).
- Ability to annotate requirements, work with APIs, vector databases, and integrate supply chain workflows with AI agents.
- APICS / CPIM / CSCP certifications are a plus.
Benefits
Comp & perks- Competitive salary
- Professional development budget
- Global team events
- Flexible working hours
- Home office setup allowance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AImachine learningNLPLLMoptimizationdata analysisdata curationdata preprocessingsupply chain analyticsdecision frameworks
Soft Skills
collaborationcommunicationproblem-solvinganalytical thinkingpresentation skills
Certifications
APICSCPIMCSCP