Implementation Engineer
6 days ago
About Zeta Services Inc.
Zeta Services Inc. is a Next-Gen Banking Tech company that empowers banks and fintechs to launch banking products for the future. Our flagship processing platform - Zeta Tachyon - is the industry's first modern, cloud-native, and fully API-enabled stack that brings together issuance, processing, lending, core banking, fraud & risk, and many more capabilities as a single-vendor stack. 20M+ cards have been issued on our platform globally.
We are actively working with the largest Banks and Fintechs in multiple global markets transforming customer experience for multi-million card portfolios. Zeta has over 1700+ employees - with over 70% roles in R&D - across locations in the US, EMEA, and Asia. We raised $280 million at a valuation from Softbank, Mastercard, and other investors in 2021.
About the Role- We are seeking a highly skilled and experienced Solution Engineer for our Conversational AI Product. The ideal candidate will be at the forefront of designing and implementing Omni-channel AI bots using low-code/no-code orchestration platforms like Yellow, Kore, Rasa etc.
- Your role will focus on translating complex banking intents into effective conversational flows and actions, optimizing user interactions with minimal coding requirements. Your expertise will drive the development of innovative, user-friendly Conversational AI experiences.
- Design and Implement: Lead the design and development of Omni-channel (voice and chat) AI chatbots using low-code/no-code platforms such as Yellow, Kore, Rasa, etc., ensuring a seamless, consistent experience across all digital touch points. Translate complex banking intents into effective and intuitive conversational flows and actions, optimizing the chatbot for ease of use and minimal manual intervention.
- LLM Response Optimization: Develop and optimize prompts for various chatbot flows against OpenI and other opensource LLMs. Develop documentation needed for Retrieval Augmented Generation for various intents. Create data sets for LLM fine tuning for intent recognition and conversation.
- Scripting: Writing small functions in Python / JS for function calling within conversational AI flows.
- Platform Mastery and Utilization: Become an expert in the features and capabilities of the chosen low-code/no-code orchestration platforms, leveraging their full potential to build sophisticated conversational AI solutions. Stay updated with the latest updates and features of these platforms to continuously improve and enhance chatbot functionalities.
- Collaboration and Stakeholder Management: Work closely with banking domain experts to understand detailed banking processes, compliance requirements, and customer service protocols, ensuring the chatbot accurately reflects and adheres to these standards. Collaborate with cross-functional teams, including UX/UI designers, project managers, and product managers, to ensure cohesive and secure implementation of chatbot solutions.
- Testing and Optimization: Conduct rigorous testing of chatbot conversations and workflows to identify and rectify any issues, ensuring high accuracy and user satisfaction. Continuously analyze chatbot interactions to identify trends, bottlenecks, and areas for improvement, optimizing conversational flows for better user engagement and efficiency.
- Documentation and Training: Create comprehensive documentation on chatbot design, architecture, and operational procedures to facilitate knowledge sharing and training. Train and support other team members on utilizing low-code/no-code platforms for chatbot development, fostering a culture of knowledge and skill development within the team.
- Domain understanding: Understand Zeta's Tachyon & 360 offering and build in-depth expertise on them. Build a deep understanding of various functionalities provided by the platform and use them in the conversational AI flows.
- Deep understanding of Bot / Conversational AI / Contact Center orchestration platforms such as Yellow, Kore, Rasa, etc.
- Programming skills in any scripting language desirable.
- Deep expertise and experience in prompt engineering and LLM Response optimization using relevant techniques.
- Understanding of Retrieval Augmented Generation and creation of documentation for RAG.
- Experience in creating data sets for LLM fine tuning.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Minimum of 2 years focused on building and maintaining Conversational AI flows.
- Certification in bot development or related technologies preferred.
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