Overview

Experience: 8 to 12 Years 1500/ Hourly
13+ Years 1500/ Hourly
Location: Hybrid (Bangalore)
Address for Bangalore Indranagar, Tanisandra
Time Zone: IST

Key Responsibilities

• Workflow Automation Development: Design, build, and deploy automated workflows for supply chain use cases, integrating AI to process and analyze regulatory data (e.g., compliance standards, tariffs, and environmental regulations).
• Impact Analysis Integration: Implement agentic systems where parameter changes (e.g., in supply chain models or regulatory thresholds) automatically initiate workflows to generate comprehensive impact analyses, including risk assessments, cost implications, and compliance checks.
• Agentic Framework Building: Leverage Python to develop autonomous AI agents capable of decisionmaking, data ingestion, transformation, and orchestration in supply chain scenarios, using frameworks like LangChain, CrewAI, or similar.
• Databricks Utilization: Utilize Databricks Mosaic for building AI/ML workflows.
• Testing and Deployment: Conduct rigorous testing of AI agents and workflows, deploy solutions in production environments, and monitor for anomalies using tools like MLflow on Databricks.
• Innovation and Research: Stay updated on emerging AI technologies for agentic systems and supply chain automation, proposing enhancements to existing processes.

Required Skills

• Education: Bachelor's or Master's degree in Computer Science, AI, Data Engineering, or a related field.
• Technical Skills:
  • 8+ years of Experience
  • Proficiency in Python for AI development, including libraries like Pandas, NumPy, Scikitlearn, and agentic frameworks (e.g., LangChain, AutoGen).
  • Strong exposure to Databricks, including building notebooks, jobs, Delta Live Tables (DLT), and integrating with cloud services (e.g., AWS, Azure).
  • Familiarity with regulatory data handling, including data governance, versioning, and compliance tools.
• Soft Skills: Excellent problemsolving abilities, strong communication skills for explaining technical concepts to nontechnical stakeholders, and a collaborative mindset.

Preferred Skills

• Certifications in AI/ML
• Exposure to containerization (Docker/Kubernetes) and CI/CD pipelines for deploying AI agents.