JAGGAER is looking to solve complex procurement and supply chain challenges across various industries by designing, building, and operationalizing data pipelines, ML models, and LLM-powered agents to transform vast structured and unstructured data into real-time, actionable intelligence for global customers.
Requirements
- Proven mastery of Python (Pandas, PySpark, scikit-learn, TensorFlow/PyTorch) and SQL.
- Deep experience with at least two enterprise platforms: OpenSearch, Snowflake, Redshift, Redis, Pinecone, SageMaker.
- Strong grounding in statistical modeling, supervised/unsupervised ML, and evaluation metrics.
- Fluency with Linux, Git, CI/CD, Docker, and orchestration frameworks (Airflow, Prefect, Kubeflow, or Dagster).
- Hands-on with LLM fine-tuning, RAG pipelines, or advanced prompt engineering.
- Cloud deployment experience (AWS Bedrock, ECS/EKS, Azure, or GCP).
- Familiarity with procurement, supply chain, ERP, or IoT sensor data.
Responsibilities
- Architect and optimize scalable ingestion, ETL/ELT, and featurestore pipelines across OpenSearch, Snowflake, Redshift, and Redis.
- Design semantic layers and vector indexes (Pinecone, OpenSearch) to power Retrieval-Augmented Generation (RAG) and Agentic AI workflows.
- Prototype, train, and evaluate predictive, prescriptive, and generative models in SageMaker and open-source frameworks.
- Implement rigorous experimentation pipelines (A/B, champion/challenger testing) and convert insights into platform features.
- Own CI/CD, monitoring, drift detection, and scalable inference for both classical ML and LLM pipelines.
- Package models into reusable microservices with Terraform, Docker, and Kubernetes.
- Orchestrate multi-agent workflows (LangGraph, CrewAI, etc.) that integrate with JAGGAER and third-party APIs.
Other
- Bachelor’s or Master’s in Computer Science, Statistics, Math, or Data Science.
- 10+ years designing and deploying production-grade ML or data engineering solutions.
- Executive communication skills—you can brief senior leadership and board-level stakeholders.
- Ability to work directly with the CDAO’s innovation team to shape the future of enterprise AI.
- Collaborate with world-class talent in a fast-paced, impact-driven culture.
