Job Summary
We are seeking a Chatbot / Conversational Architect to own the end-to-end architecture, design, and governance of intelligent conversational solutions across our Banking and Financial Services platforms.
This role is responsible for defining secure, scalable, compliant, and reusable conversational frameworks that enhance customer experience, improve operational efficiency, and support digital transformation initiatives. The architect will work closely with engineering, cybersecurity, compliance, and business stakeholders to ensure chatbot solutions meet enterprise, regulatory, and customer expectations.
Key Responsibilities: Conversational AI Architecture & Design
- Define and own enterprise-grade conversational AI architectures, reference models, and design standards for banking use cases, including account services, loan servicing, fraud notifications, and financial guidance
- Lead architecture design for LLM-powered chatbots, including intent-based, hybrid, and generative conversational flows
- Design scalable, resilient, and observable chatbot platforms with appropriate fallback, escalation, and human-in-the-loop mechanisms
Integration & Platform Engineering
- Architect secure integrations with core banking systems, CRM platforms, KYC/AML systems, data platforms, and digital channels (web, mobile apps, IVR, messaging platforms)
- Define API, event-driven, and microservices integration patterns for conversational solutions
- Guide cloud-native deployments with a preference for Microsoft Azure, ensuring high availability and performance.
Security, Compliance & Governance
- Ensure chatbot solutions are compliant-by-design with financial regulations and data privacy standards (GDPR, PCI DSS, RBI guidelines, SOC2)
- Implement data protection, PII masking, authentication, authorization, and consent management mechanisms
- Define governance frameworks for LLM usage, including prompt lifecycle management, model explainability, auditability, bias mitigation, and hallucination control
Optimization, Analytics & Quality Assurance
- Establish testing and validation frameworks for accuracy, security, compliance, and customer experience
- Define and monitor key performance indicators such as containment rate, response latency, escalation accuracy, customer satisfaction, and model drift
- Drive continuous optimization using analytics, A/B testing, and feedback loops
Collaboration & Thought Leadership
- Partner with compliance, cybersecurity, legal, product, customer service, and engineering teams to align conversational AI initiatives with enterprise goals
- Provide architectural guidance and mentorship to development teams
- Stay current with advancements in conversational AI, LLMs, fintech innovation, and regulatory technology.
Required Qualifications, Skills & Experience
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or a related field
- 812 years of overall IT experience, with 35 years in Conversational AI / AI Architecture
- 35 years of experience in Banking or Financial Services, working in regulated environments
- Hands-on experience with chatbot frameworks such as Microsoft Bot Framework, Rasa, Kore.ai, and NLP platforms like Dialogflow or LUIS.
- Strong expertise in LLMs, intent recognition, entity extraction, context management, and RAG architectures.
- Proficiency in Python, JavaScript, or other relevant programming languages
- Experience with cloud platforms (Azure preferred), RESTful APIs, and secure data handling
- Thorough understanding of banking workflows, customer service operations, and financial product lifecycles
- Experience implementing monitoring, analytics, and optimization strategies for conversational system
Preferred Qualifications
- Experience delivering multilingual and omnichannel conversational AI solutions
- Background in fraud detection, risk scoring, or financial advisory chatbot
- Knowledge of voice banking and IVR-based conversational systems
- Certifications in AI/ML, cloud architecture (Azure), or fintech platforms
- Experience with GenAI governance frameworks and open-source vs managed LLM platforms
What Success Looks Like in This
- RoleSecure, compliant, and scalable chatbot platforms adopted across banking channels
- Improved customer experience, containment rates, and operational efficiency
- Strong governance and risk controls for GenAI and LLM usage
- A reusable conversational AI architecture supporting future innovation.
