Conversational AI - Architect

• 10+ years of industry experience
• 4+ years experience developing and deploying

  conversational virtual assistants

• 4+ years hands-on experience utilizing platforms like

  Amazon Lex, Google Dialogflow, IBM Watson, Microsoft Bot Framework, Kore.AI, Rasa, or Clinc

• 2+ years hands-on experience

  building Gen AI applications

  using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures including setting up vector databases and prompt engineering
• Fluency in writing code in

  Python, JavaScript, C++

  or some other high-level language
• Experience designing

  multi-agent collaboration workflows

  (e.g., planner-executor, tool-selector).
• Familiarity with

  agent memory types

  (episodic, declarative, semantic) and persistent context handling.
• Experience building

  observability dashboards and metrics for LLM/agent execution

  (e.g., prompt logs, traces, outcomes).
• Ability to translate user and business requirements into high-performing agent behaviors.
• Passion for emerging trends in Agentic AI, autonomous reasoning, tool augmentation, and GenAI-driven automation.
• Knowledge and understanding of Artificial Intelligence (AI) disciplines such as

  Machine Learning or Natural Language Processing

• Experience with Artificial Intelligence (AI) industry trends and business applications
• Solid understanding of conversational dialog systems, natural language processing (NLP) fundamentals, and machine learning
• Familiar with utterances, entities, intents, classification, annotation, business rules and APIs
• Experience designing, developing and deploying large training data sets
• Strong understanding on data management and annotation processes
• Must come financial services/capital markets/investment banking
• Excellent Analytical skills
• Great interpersonal and communication skills
• Open to work in UK Shift (10 Am to 9 Pm IST with 8 hours of productive work)

Responsibilities:

• Design and implement Agentic AI workflows that autonomously orchestrate tasks using tool calling, memory, planning, and execution capabilities.
• Architect end-to-end Conversational AI solutions integrated with LLMs, using platforms such as Dialogflow, Rasa, Lex, and others

• Partner with various partners including PM's, PO's UX designers and content strategist to plan, validate and execute the model and implementation of conversational experiences within the virtual assistant
• Develop and enhance model training and optimization processes with a focus on driving scalability and automation
• Develop tool schemas, action mappers, and execution logic to enable intelligent decision-making across diverse APIs and data sources.
• Lead model analysis via testing, misclassification prioritization, root cause assessment
• Define and implement the "intents" and "entities" that define the conversation interaction, along with the associated business rules, logic and API interactions that are required for sophisticated interactions
• Responsible for building human language data sets to train machine learning models driving the virtual assistant.
• Work closely with other members of the product team and technology partners to identify enhancements to the conversational experiences
• Act as a liaison between our AI Product team and Technology to ensure that our Virtual Assistant delivers intelligent and intuitive conversations, resulting in great customer experience

Education Qualification: