AI Implementation Engineer

As an AI Implementation Engineer, you will be responsible forintegrating, optimizing, and deploying AI/ML solutions that enhance banking intelligence, automation, and fraud detection. Whether youre working on backend systems, frontend AI-powered interfaces, or full-stack AI implementations, your contributions will help shape the future of AI-driven banking.

Responsibilities

• Develop & deploy AI/ML models for banking, payments, and fraud detection.
• Integrate AI-powered decision-making into real-time banking systems.
• Optimize AI pipelines for scale, latency, and security.
• Leverage NLP, Computer Vision, or Generative AI to build intelligent banking solutions.
• Work with engineering teams to productionize AI solutions within Zeta s platform.
• Use MLOps best practices to ensure seamless AI model deployment, monitoring, and scaling.
• Mine TBs of transaction data to generate insights and improve predictive capabilities.
• Experiment with AI-driven user experiences (chatbots, voice assistants, Copilot-like interfaces).
• Ensure AI models comply with regulatory and security standards.

Skills

• Must have 1-5 years experience in building AI Tools and working on Copilot, PowerApps. Past projects should be included in github.
• Strong AI/ML experience (training, deploying, and scaling models in production).
• Proficiency in Python, TensorFlow, PyTorch, or scikit-learn.
• Experience with ML model deployment (Docker, Kubernetes, MLflow, or similar).
• Knowledge of MLOps pipelines, versioning, and monitoring.
• Experience working with large datasets, feature engineering, and model tuning.
• Understanding of Generative AI, NLP, or Computer Vision.
• Ability to integrate AI solutions into backend or frontend applications.
• You must have your github / repo links on your resume to showcase your past projects.

Role: Data Science & Machine Learning - Other

Industry Type: IT Services & Consulting

Department: Data Science & Analytics

Employment Type: Full Time, Permanent

Role Category: Data Science & Machine Learning

Education

UG: Any Graduate

PG: Any Postgraduate