AI practice Lead for GCC

About Kagool    We are a fast-growing IT consultancy specialising in the transformation of complex Global enterprises. We are looking for enthusiastic and hardworking individuals that to help deliver for our global customer base. We embrace the opportunities of the future and work proactively to make effective use of technology. As you can imagine, this means that we have a vibrant and diverse mix of skills and people making Kagool a wonderful place to work.   About the Role We are seeking an AI Practice Lead to head our Artificial Intelligence practice covering India and UAE. The individual will be responsible for driving Sales, Pre-Sales, Architecture, Delivery, R&D and POC activities across Generative AI, Machine Learning, and Advanced Analytics. The ideal candidate will combine deep technical expertise with commercial and leadership skills, guiding teams to innovate, optimise, and scale AI-driven initiatives for our customers globally. Key Responsibilities · Lead the design and implementation of Generative AI and Data Science solutions using LLMs (GPT, Claude, Gemini, etc.), machine learning models, and multimodal systems. · Engage with customers to identify opportunities, define use cases, and demonstrate value through AI-driven solutions and POCs. · Support sales and pre-sales teams in developing proposals, estimates, and solution blueprints, articulating the business value of AI solutions. · Architect and oversee delivery of AI and ML projects leveraging Azure AI, Azure OpenAI, Databricks, Hugging Face, LangChain, and RAG frameworks. · Lead R&D initiatives to evaluate new AI technologies and frameworks, and translate them into enterprise-ready offerings. · Guide the design and deployment of AI workflows using Python, PyTorch, TensorFlow, or Hugging Face frameworks. · Work with data scientists, ML engineers, and product teams to develop models for applications such as text generation, summarization, image synthesis, forecasting, chatbots, and enterprise automation. · Collaborate with DevOps/MLOps teams to ensure deployment, monitoring, and governance of AI models in production environments. · Optimise model performance, cost, and accuracy through prompt engineering, model tuning, and vector-based retrieval pipelines. · Mentor and guide junior engineers and data scientists in AI technologies, best practices, and delivery excellence. · Represent Kagool in client meetings, industry events, and thought leadership forums. Required Skills & Qualifications · Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field. · 10+ years of experience in AI/ML or Data Science, with at least 3 years in a leadership or practice management role. · Strong experience in customer engagement, pre-sales, and solution delivery across AI and Data Science domains. · Excellent communication, leadership, and stakeholder management skills with the ability to influence at senior levels. Experience and Technical Skills Generative AI / LLM Experience · Proven experience in developing and deploying solutions using LLMs such as GPT, Claude, Gemini, or Mistral. · Hands-on knowledge of LangChain, Hugging Face, OpenAI API, and Azure OpenAI. · Expertise in building RAG (Retrieval-Augmented Generation) pipelines and multi-agent architectures. · Strong understanding of embeddings, vector databases (Pinecone, FAISS, Chroma, Weaviate), and prompt engineering. · Experience developing generative applications such as chatbots, summarization, code generation, and content automation. · Familiarity with fine-tuning, cost optimisation, and performance evaluation of LLMs in production. · Exposure to GenAI frameworks, model governance, AI ethics, and responsible AI design. Machine Learning / Data Science Experience · Strong knowledge of classical and deep learning techniques including regression, classification, clustering, NLP, and time-series forecasting. · Hands-on experience in data preparation, feature engineering, and model lifecycle management. · Expertise in ML frameworks such as Scikit-learn, TensorFlow, and PyTorch. · Experience in building and deploying ML models in Azure, leveraging Azure Machine Learning, Databricks, and Synapse. · Knowledge of MLOps tools such as Azure DevOps, Docker, Kubernetes, and CI/CD pipelines for model deployment. · Experience in integrating ML insights into business applications and decision support systems. · Familiarity with Power BI, Azure Data Studio, and visualization techniques for communicating insights. Preferred Qualifications · Experience in building reusable assets, accelerators, or frameworks for AI delivery. · Familiarity with AI orchestration platforms and agentic frameworks. · Knowledge of data privacy, compliance, and AI regulatory standards. · Contributions to open-source AI projects or published research papers. Career at Kagool   A career at Kagool will give you a path towards progression and opportunities, with the current rate of growth we at Kagool have dedicated time towards individual growth, recognizing individual contributions, filling the team with a keen sense of purpose along with providing a fun, flexible and friendly work environment.