Job
Description
Associate Director of Engineering - Conversational AI Location: Bangalore, India Our AI Data Division plays a pivotal role in this transformation, driving cutting-edge research and large-scale deployment of Large Language Models (LLMs), Generative AI, Conversational AI, and advanced Data Analytics . By harnessing AI-powered automation, intelligent search, and predictive analytics, we are building scalable, high-impact solutions that enhance customer interactions, optimize business processes, and unlock new opportunities across the company s ecosystem. Department Overview The Conversational Experiences Department (CXD) is dedicated to building production-ready, scalable, and high-performance AI systems that redefine Conversational AI. Our focus is on: Conversational AI Frameworks - Traditional NLP-powered chatbots, AI-driven search, and multi-modal assistants. Next-Generation GenAI Platforms - LLM-powered chat experiences, voice and multi-modal AI, real-time response generation. AI Engineering at Scale - Deploying robust AI models in production environments, ensuring high availability, low latency, and enterprise-grade security . We are looking for a technical leader who brings deep expertise in both AI/ML algorithms and scalable engineering systems someone who has built traditional Conversational AI platforms and is now transitioning to GenAI-driven, multi-modal AI solutions . Position Overview As Associate Director of Engineering - Conversational AI , you will lead a team of AI engineers and software architects to develop and scale enterprise-grade Conversational AI systems . This role requires expertise in AI model development, cloud-scale engineering, and production readiness . This is an engineering-first leadership role , with a strong algorithmic focus on NLP, LLMs, and Deep Learning models . The ideal candidate has hands-on experience designing and deploying AI-powered applications in high-traffic, real-time environments. Key Responsibilities 1. AI Productization Engineering Leadership Lead development of Next Generation LLM/ Multimodal driven Chatbots IVR using Agentic Frameworks Architect and develop Conversational AI systems that are highly scalable, secure, and efficient . Oversee MLOps/ LLMOps pipelines , AI deployment, and cloud-native architectures, optimizing AI workloads for latency, accuracy, and cost efficiency . 2. Algorithmic Advancements Model Innovation Drive end-to-end development of AI/ML models , from data collection to inference optimization . Develop and optimize multi-modal AI models that combine text, voice, and visual inputs . Implement advanced Retrieval-Augmented Generation (RAG) techniques and Reinforcement Learning for AI-driven conversations . 3. Engineering Excellence Production Readiness Ensure low-latency, high-availability AI services that scale to millions of users. Design cloud-based microservices architectures for AI applications using Kubernetes, Docker, and serverless computing . Optimize LLM inference with quantization, distillation, and model caching techniques to reduce compute costs and improve performance. Ensure the engineering team delivers high-quality software solutions that adhere to defined production SLOs and maintain high standards of quality and reliability. 4. Leadership Team Development Build, mentor, and scale a high-performance AI engineering team , fostering innovation and technical excellence. Drive cross-functional collaboration with product, UX, and data science teams to align AI capabilities with business goals. Establish best practices for CI/CD in AI development, automated model retraining, and continuous evaluation frameworks . 5. Collaboration Collaborate extensively with Product Project Management, and Customer Success Management to ensure a seamless alignment between engineering output and overall business strategy Mandatory Qualifications 15+ years of software engineering experience, including 5+ years in AI/ML leadership roles . Deep expertise in: Conversational AI NLP (LLMs, Transformers, RNNs, Semantic Search) GenAI Frameworks (GPT-4, Claude, Llama, Gemini, Hugging Face, LangChain. Langgraph) AI Model Deployment at scale (TensorFlow, PyTorch, ONNX, OpenAI API) Cloud Platforms (GCP, Azure, AWS) and MLOps pipelines (Kubeflow, MLflow) AI-Powered Search (vector databases, semantic search, retrieval-based chat) Microservices development - Java, Python, Spring Boot, NoSQL, Distributed Systems Experience building and deploying large-scale, production AI systems in high-traffic environments. Strong leadership, with the ability to hire, mentor, and scale AI engineering teams . Preferred Qualifications Experience in both traditional Conversational AI and next-gen GenAI-based assistants Expertise in AI-driven personalization, AI safety, and responsible AI practices Strong software architecture knowledge , including microservices, distributed computing, and API-driven AI deployment Experience working in startups or high-growth AI-first organizations , leading AI-driven transformation ,
