Job Summary:
JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes. They are hiring an Architect, Data AI to lead the AI/ML initiatives, architect production-grade AI systems, and collaborate with product and engineering teams to deliver measurable AI outcomes.
Responsibilities:
• Set and own the AI/ML technical strategy for the platform — from model architecture to evaluation, deployment, and monitoring — and rally engineering and product leadership around it.
• Design, develop, and deploy machine learning models for prediction, classification, clustering, and time-series analysis.
• Develop Generative AI and LLM-powered solutions, including RAG pipelines for knowledge retrieval and contextual responses.
• Build and optimize Agentic AI systems capable of multi-step reasoning, tool orchestration, and autonomous workflows.
• Architect and manage vector database solutions (e.g., Pinecone, Weaviate, FAISS, Milvus) for embeddings, hybrid search, and RAG pipelines.
• Leverage advanced statistical and data science techniques to extract actionable insights from structured and unstructured datasets.
• Implement and scale AI/ML pipelines using AWS services (SageMaker, Lambda, API Gateway, Bedrock, S3, EKS).
• Set the technical bar for the data science / ML function — design reviews, code and model reviews, technical standards, and upskilling peers and engineers around AI/ML best practices.
• Partner with business, product, and engineering leaders to translate procurement and supply chain problems into measurable AI/ML solutions.
• Write efficient, modular, and maintainable Python code for modeling, data processing, and deployment.
• Use advanced SQL for querying, transforming, and analyzing large relational datasets.
• Establish standards for model evaluation, observability, and responsible AI — including documentation, reproducibility, and guardrails for LLM and agent systems.
Qualifications:
Required:
• 14–15 years of experience in data science / applied ML, including 3–4 years building production Generative AI and Agentic AI systems with LangChain, LangGraph, and LangFlow.
• Track record of technical leadership without direct reports — setting architecture, driving cross-team alignment, and shipping AI/ML into production at enterprise scale.
• Proven expertise in conventional ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling.
• Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and Agentic AI solutions.
• Experience with LangChain, LangGraph, LangFlow, or similar agent frameworks.
• Strong proficiency in Python for machine learning, data manipulation, and deployment.
• Advanced SQL skills for working with large relational datasets, including hands-on experience with Snowflake (warehousing, performance tuning, and integration with ML/AI pipelines).
• Hands-on experience with AWS services (SageMaker, Bedrock, Lambda, EKS, API Gateway, S3).
• Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus) as a core component of RAG pipelines.
• Familiarity with data engineering principles and cloud-based data pipelines.
• Strong judgment translating ambiguous business problems into concrete AI/ML solutions — and the discipline to know when ML is the wrong tool.
Preferred:
• Exposure to Model Context Protocol (MCP) for orchestrating AI applications.
• Background in MLOps/CI-CD pipelines for deploying and monitoring ML models at scale.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch) for advanced modeling.
Company:
Jaggaer is SaaS that manages spending, suppliers, contracts, sourcing, shopping, inventory and accounts payable of businesses. Founded in 1995, the company is headquartered in Cary, USA, with a team of 1001-5000 employees. The company is currently Late Stage.