About the Role
Seeking an experienced Agentic AI Developer to design, develop, and deploy intelligent AI agents that automate business processes, enhance customer experiences, and drive operational efficiency. The ideal candidate will have strong expertise in Agentic AI systems, AI agent development, Databricks, LLM orchestration, harness engineering, and loop engineering, along with a solid Computer Science foundation.
Key Responsibilities
Agentic AI Development
Design, build, and deploy autonomous and semi-autonomous AI agents using modern Agentic AI frameworks.
Develop multi-agent workflows for complex business processes and decision-making systems.
Implement agent reasoning, planning, memory management, and tool-calling capabilities.
Build scalable AI solutions leveraging Large Language Models (LLMs).
AI Agent Development
Develop AI agents using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LangChain, or similar technologies.
Integrate external APIs, enterprise systems, and knowledge repositories into agent workflows.
Design Retrieval-Augmented Generation (RAG) solutions to improve agent performance and accuracy.
Harness Engineering
Build and maintain evaluation harnesses for AI agents and LLM applications.
Create automated testing frameworks for agent performance, reliability, safety, and scalability.
Establish benchmarks and quality metrics for AI agent deployments.
Monitor model performance and implement continuous evaluation pipelines.
Loop Engineering
Design Human-in-the-Loop (HITL) architectures for AI governance and decision validation.
Build feedback loops to improve agent accuracy and learning outcomes.
Implement workflow orchestration and agent lifecycle management.
Develop monitoring mechanisms to ensure responsible AI operations.
Databricks & Data Engineering
Develop and deploy AI solutions using Databricks Lakehouse Platform.
Work with structured and unstructured data for AI model development and optimization.
Utilize Databricks notebooks, workflows, MLflow, Delta Lake, and Unity Catalog.
Collaborate with data engineering teams to build scalable AI data pipelines.
Software Development & Integration
Develop production-grade applications using Python and modern software engineering practices.
Build REST APIs and microservices for AI agent integration.
Implement CI/CD pipelines and MLOps best practices.
Ensure security, compliance, and governance standards within enterprise AI implementations.
Required Qualifications / Education
Bachelor's or master's degree in: Computer Science
