Role Overview :

We are seeking a hands-on AI/ML Engineer with proven expertise in designing, building, and deploying intelligent chatbots.

The ideal candidate will not only be technically strong but also capable of leading a small team of junior engineers, setting technical direction, and ensuring high-quality delivery.

Key Responsibilities :

- Architect, design, and implement AI-driven chatbot solutions using state-of-the-art frameworks (e.g., Rasa, Dialogflow, LangChain, LLM APIs).

- Apply Natural Language Processing (NLP) and Machine Learning techniques for intent classification, entity recognition, and conversation management.

- Lead end-to-end chatbot development lifecycle from data preparation and model training to deployment and monitoring.

- Guide junior engineers through code reviews, mentorship, and technical leadership.

- Collaborate with product, UX, and business teams to ensure chatbot solutions meet user and business requirements.

- Continuously evaluate and integrate new tools, frameworks, and AI advancements (e.g., LLM fine-tuning, vector databases, prompt engineering).

- Ensure production-grade performance, scalability, and security of deployed solutions.

Required Skills & Experience :

- 610 years of professional experience in AI/ML and software engineering, with at least 3+ years building chatbot solutions.

- Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, spaCy, Hugging Face, etc.).

- Strong expertise in NLP techniques, conversational AI frameworks (Rasa, Dialogflow, Botpress, LangChain, etc.), and LLM APIs (OpenAI, Anthropic, etc.).

- Experience with cloud deployment (AWS/Azure/GCP) and containerization (Docker/Kubernetes).

- Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus) for retrieval-augmented generation (RAG).

- Hands-on experience integrating chatbots with enterprise systems, APIs, and messaging platforms (Teams, Slack, WhatsApp, Web, etc.).

- Strong understanding of ML lifecycle management (MLOps), model deployment, monitoring, and retraining.

- Demonstrated ability to lead small technical teams and deliver projects in Agile environments.

Nice-to-Have :

- Experience in Generative AI (LLMs, fine-tuning, prompt engineering).

- Background in analytics, recommendation systems, or voice-enabled bots.

- Open-source contributions or published work in chatbot/AI.