Job Responsibilities :

- Develop and implement AI and Agentic AI solutions that enhance customer engagement, sales effectiveness, and operational efficiency across enterprise CRM platforms.

- Build intelligent workflows using Large Language Models (LLMs), enterprise data, and tool integrations to automate customer and business processes.

- Develop production-ready GenAI applications, including Retrieval-Augmented Generation (RAG), prompt engineering, and AI-powered business workflows.

- Build and maintain scalable data pipelines and AI solutions using Google Cloud Platform (GCP) services such as BigQuery, Composer (Airflow), DataProc, and related cloud services.

- Integrate AI applications with enterprise systems, APIs, and data platforms while ensuring operational reliability and performance.

- Collaborate with product managers, software engineers, data engineers, and business stakeholders to translate business requirements into AI-enabled solutions.

- Contribute to shared AI frameworks, reusable components, evaluation pipelines, and engineering standards.

- Ensure AI applications comply with enterprise security, governance, responsible AI, and operational standards.

Required Skills / Experience :

- Experience with Agentic AI concepts, including orchestration frameworks, tool calling, context management, or multi-step AI workflows.

- Understanding of Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, and LLM evaluation techniques.

- Strong programming skills in Python and experience developing backend services, APIs, and data pipelines.

- Experience with AI/ML frameworks such as LangChain, LangGraph, PyTorch, TensorFlow, or Scikit-learn.

- Working knowledge of Google Cloud Platform (GCP), including BigQuery, Composer (Airflow), DataProc, Cloud Storage, and related data services.

- Understanding of cloud-native application development, distributed systems, and modern software engineering practices.

- Knowledge of CI/CD, containerization (Docker), and production deployment concepts.

Qualifications :

- 35+ years of experience in software engineering, machine learning engineering, data engineering, or applied AI.

- Hands-on experience building or integrating GenAI applications using Large Language Models (LLMs).