Description

Design and deploy autonomous agentic AI systems that integrate with enterprise infrastructure.

Responsibilities

• Architect agentic workflows using LangChain, LangGraph, or CrewAI, implementing multi-step planning and tool-use capabilities.
• Build and maintain LLM-powered agents with memory, self-correction mechanisms, and adaptive behaviors in production.
• Develop automation pipelines that connect agentic AI with enterprise tools like ServiceNow and Databricks.
• Implement MLOps practices for model deployment, monitoring, and lifecycle management across cloud and on-premise environments.
• Collaborate with IT Service Continuity and business teams to align automation initiatives with operational requirements.

Required Skills

• 8+ years of hands-on Python development experience.
• Proven production experience building LLM-powered agentic systems.
• Strong proficiency with AI/ML frameworks, specifically LangChain Development.
• Experience with vector databases (Pinecone, ChromaDB, or Weaviate) and memory-enabled workflows.
• Practical knowledge of cloud platforms (Azure, GCP, or AWS) for deploying AI pipelines.
• Experience with containerized deployments using Docker and Kubernetes.
• Familiarity with prompt engineering, model evaluation, and optimization techniques.
• Strong debugging skills for distributed systems and asynchronous agentic workflows.

Preferred Skills

• Experience integrating agents with enterprise ITSM tools like ServiceNow and Jira.
• Background in Databricks for data engineering and ML workflow orchestration.

Key Skills

Education

Any Graduate