Leading end-to-end strategy and implementation of GenAI-powered conversational solutions across chat and voice interfaces for enterprise clients. (Leading multiple projects where I apply GenAI techniques and LLM fine-tuning (using models like OpenAI, Azure OpenAI, and Anthropic) to solve business challenges in customer support, self-service, and automation.)

Designing and refining prompt engineering frameworks tailored to LLMs such as OpenAI, Azure OpenAI, and Anthropic.

Advising clients on migrating from traditional NLU-based bots to GenAI-enabled assistants, including hybrid architectures that balance control and creativity.

Analyzing user behavior, performance metrics, and containment trends to optimize conversation flows and align assistant behavior with business KPIs.

Identifying LLM capability gaps and designing mitigation strategies, including fallback prompts, fine-tuned flows, and guardrail mechanisms.

Collaborating with cross-functional teams (product, UX, NLP, engineering) to ensure scalable, adaptive, and user-centric assistant performance.

Training enterprise clients on Kore.ai’s platform, with a focus on its NLP engine, GenAI features, and conversation analytics dashboards.

Supporting clients across diverse sectors—banking, healthcare, travel, e-commerce, insurance, and IT services—with strategic GenAI adoption plans.

As Manager of the NLP Team within the Professional Services division at Kore.ai, I led a team of NLP Analysts and Conversation Designers in delivering custom chatbot and voicebot solutions for enterprise clients across industries such as healthcare, banking, travel, insurance, and e-commerce. In parallel, I also served as the NLP Lead and Strategist for key client projects—owning the end-to-end NLP execution plan to ensure virtual assistants met business goals and delivered measurable outcomes.

Key responsibilities included:

Defining NLP strategies for client implementations—outlining techniques, processes, and phased roadmaps for deployment, testing, and optimization.

Leading discovery sessions with cross-functional stakeholders to understand business objectives, user journeys, and domain-specific language, and translating them into scalable NLU architectures.

Overseeing bot training workflows, including intent taxonomy design, entity modeling, context and disambiguation handling, sentiment-driven responses, and multilingual configuration.

Guiding NLP testing and go-live readiness, including utterance analysis, test planning, regression reviews, and performance benchmarking.

Mentoring and managing a high-performing NLP team, ensuring timely delivery, knowledge sharing, and alignment with client and platform standards.

Introducing GenAI and LLM capabilities into existing NLU-based solutions—enabling use cases like auto-response generation, summarization, dynamic prompting, and knowledge grounding.

Working with LLMs such as OpenAI and Azure OpenAI to enhance assistant intelligence and support hybrid GenAI+NLU implementations.

Driving performance improvement initiatives by leveraging user analytics, conversation data, and containment metrics for continuous tuning.

Collaborating with product, engineering, and UX teams to ensure solutions were robust, scalable, and aligned with Kore.ai’s platform capabilities.