Job Description
Zeta is a Next-Gen Banking Tech company that empowers banks and fintechs to launch innovative, AI-powered banking solutions. Founded by Bhavin Turakhia and Ramki Gaddipati in 2015, we are redefining banking infrastructure with a modern, cloud-native stack.
Our flagship processing platform – Zeta Tachyon – integrates issuance, processing, lending, fraud & risk, and core banking into a single, API-first ecosystem. With 20M+ cards issued globally, we work with the world’s largest banks and fintechs to transform customer experiences.
Zeta has over 1,700+ employees across the US, EMEA, and Asia, with 70%+ roles in R&D. Backed by SoftBank, Mastercard, and other investors, we raised $330M at a $2B valuation in 2025.
About Role :
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 you're 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 Java, Springboot, 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.
Zeta is an equal opportunity employer.
- At Zeta, we are committed to equal employment opportunities regardless of job history, disability, gender identity, religion, race, marital/parental status, or another special status. We are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the roles and responsibilities.
