We are looking for a highly experienced Senior Agentic AI Developer to design, build, and deploy advanced AI-driven solutions focused on large-scale contact center transcript analysis. The role requires strong expertise in Python, Snowflake, and modern Agentic AI frameworks to develop intelligent systems that generate summaries, insights, classifications, and business reports from structured and unstructured data.

The ideal candidate should be capable of independently driving end-to-end AI solution deliveryfrom understanding business requirements to architecture, development, deployment, and optimization.

Shift : 2 PM - 11 PM

Key Responsibilities :

- Design, develop, and deploy Agentic AI solutions for analyzing large-scale contact center transcripts.

- Build AI agents capable of generating summaries, insights, classifications, and automated business reports.

- Develop robust Python-based data processing pipelines and AI workflows.

- Work extensively with Snowflake to manage, process, and analyze large volumes of structured and unstructured data.

- Translate complex business requirements into scalable and production-ready AI solutions.

- Implement and optimize LLM-based applications including RAG (Retrieval-Augmented Generation) systems.

- Design prompt engineering strategies for improving AI agent accuracy and performance.

- Collaborate with stakeholders to define AI use cases and deliver end-to-end solutions independently.

- Ensure performance, scalability, and reliability of deployed AI systems.

Required Skills & Experience :

- 9+ years of experience in software engineering or data engineering roles.

- Strong hands-on expertise in Python and Snowflake.

- Proven experience in Agentic AI, LLMs, RAG architectures, and Prompt Engineering.

- Familiarity with AI orchestration frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar tools.

- Strong understanding of NLP (Natural Language Processing) and text analytics techniques.

- Experience working with large-scale datasets and building scalable data pipelines.

- Knowledge of cloud platforms such as AWS, Azure, or GCP.

- Ability to independently own projects and deliver end-to-end AI solutions.