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Mumbai metro and broad ML/platform skill requirements create moderate applicant density and competition.
Specialized ML/GenAI platform expertise and MLOps experience make background transferability limited across industries.
Clear 8+ years and 3+ years management plus mandatory LLM, MLOps, Kubernetes and vector DB skills tighten filters.
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Lead and manage a cross-functional engineering team focused on designing and delivering next-generation AI and Generative AI platforms, ensuring scalability, security, and integration into global consulting services.
Own the AI platform roadmap from experimental models to enterprise-grade solutions supporting RAG, agentic workflows, and automated model fine-tuning at scale.
Oversee technical architecture and ensure production readiness of platforms involving LLMs, MLOps pipelines, vector databases, and multi-cloud environments, maintaining compliance with global security and Responsible AI standards.
8+ years experience in data/software domain with at least 3+ years in people management or technical leadership of Data Science or ML teams.
Hands-on experience with LLMs (OpenAI, Claude, Llama) and complex RAG architectures implementation.
Strong expertise in Kubernetes, Docker, and cloud-native AI services (AWS Bedrock/SageMaker, Azure AI, or Google Vertex AI).
Bachelor’s or Master’s degree in Data Science, Computer Science, AI, or related quantitative field; position based onsite in Mumbai.
Experienced engineering leader bridging data science research and scalable software platform delivery in AI/ML contexts, especially with LLMs and generative AI.
Strong operational ownership of AI/ML platform products focusing on production readiness, reliability, cost-efficiency, and developer experience.
Skilled at managing global, distributed teams using Agile methodologies and aligning cross-functional stakeholders including product managers and cloud architects.