Architect, Data AI

JAGGAER provides an intelligent Source-to-Pay and Supplier Collaboration Platform that empowers organizations to manage and automate complex processes while enabling a highly resilient responsible and integrated supplier base. With 30 years of expertise we specialize in solving complex procurement and supply chain challenges across various industries.

Our 1300 global employees are obsessed with ensuring customers get full value from our products - ultimately enhancing and transforming their businesses. For more information visit

We are hiring a Architect Data AI to lead the next generation of AI/ML across JAGGAERs Source-to-Pay and Supplier Collaboration platform. Youll set the technical direction across conventional ML Generative AI LLMs Agentic AI and RAG and ship those capabilities into products used by 1300 enterprise customers and the global supply chains they run.

This is a hands-on technical leadership role. You will architect production-grade AI systems raise the technical bar across data science and ML engineering and partner directly with product engineering and customer-facing leaders to translate procurement and supply chain problems into measurable AI outcomes spend intelligence supplier risk contract understanding autonomous sourcing workflows and beyond.

What Success Looks Like in 12 Months:
A production agentic workflow live in the JAGGAER platform automating a meaningful step of a customers source-to-pay process.
At least one Generative AI / RAG capability shipped to customers with measurable adoption and a clear quality bar (groundedness latency cost per call).
A documented AI/ML strategy and roadmap for the function prioritized against business outcomes with buy-in from product and engineering leadership.

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.

1415 years of experience in data science / applied ML including 34 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 Qualifications (Good-to-Have)
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.

What We Offer:
At JAGGAER we are committed to supporting you and your familys well-being. Your health is a priority and we offer a range of programs to help you stay well and thrive. Our
benefits include Health Accidental Insurance and Term Life.

Our Values - T.E.A.M
At JAGGAER our business is about people. Our products are built on intellectual property but the real differentiator is the teams behind themthe way we collaborate innovate solve problems and deliver for customers. TEAM gives us a common set of expectations for how we work together across products cultures and geographies.
Transparency - Openness Builds Trust:
Candor strengthens relationships speeds decision-making and ensures problems are solved togetherwith customers teammates and partners.
Entrepreneurial Spirit Own It Drive It Make It:
A scrappy customer-obsessed problem-solving mindset is at the cornerstone of both organizational and personal growth
Accountability Thumbs In Not Fingers Out:
We take responsibility for ourselves before pointing elsewhere
Metrics-Driven Results Outcomes Over Activities:
Data and evidence guide our decisions help us course-correct quickly and ensure were delivering real impact.

EEO:
JAGGAER is a proud equal opportunity/affirmative action employer supporting workforce diversity. We do not discriminate based upon race ethnicity ancestry religion color national origin sex (including pregnancy childbirth or related medical conditions) marital status caregiver status sexual orientation gender gender identity gender expression transgender status sexual stereotypes age genetic information military or veteran status mental or physical disability or other applicable legally protected characteristics.

ACCESSIBILITY:
JAGGAER is committed to providing access and reasonable accommodation to applicants. If you are a qualified individual with a disability or a disabled veteran and you think you may require an accommodation for any part of the recruitment process please send a request to: All requests for accommodations are treated discreetly and confidentially as practical and permitted by law.

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