AI/ML Engineer

Key Responsibilities

• Design and develop AI/ML models for banking automation and operational insights.

• Build and maintain chatbots using modern LLMs such as Gemini.

• Implement robust Python applications for data processing, prediction pipelines, and automation tasks.

• Collaborate with banking operations teams to understand processes and convert them into ML/AI-driven solutions.

• Provide production support, monitor model performance, and execute root-cause analysis for AI systems.

• Work with structured/unstructured datasets and perform data processing using tools like Apache Spark.

• Integrate models into enterprise applications using REST APIs, version control (Git), and CI/CD pipelines.

• Develop backend components in Java and C programming when required for system integration.

• Work with cloud environments including Amazon DynamoDB for scalable data storage.

• Collaborate with cross-functional teams including Agents, developers, data scientists, and support engineers.

Required Technical Skills

• Strong experience with AI, Machine Learning, and LLMs.

• Hands-on Python programming for AI, ML, automation & backend.

• Chatbot development (LLM-based, rule-based).

• Banking operations domain knowledge (customer onboarding, KYC, AML, workflows).

• Experience working with API design and integration.

• Strong Linux & Production Support troubleshooting skills.

• Experience with Git and other version control systems.

• Programming exposure to:

  • C Programming

  • Java

  • Python

• Data Engineering/Processing with:

  • Spark

  • File-based workflows

  • Real-time or batch pipelines

• Experience working with Agents, AI orchestration tools, and multi-model pipelines.

• Cloud experience including Amazon DynamoDB.