Manager - Data Engineering

• Lead the design, execution, and scaling of end-to-end AI/ML and GenAI initiatives, including LLM fine-tuning and continuous optimization in production.
• Drive the integration of advanced AI/ML models (classical ML models and GenAI models like GPT, Claude, and other LLMs via APIs from OpenAI, Anthropic, AWS Bedrock, etc.) into key business workflows.
• Oversee the development of RAG pipelines, embeddings-based search systems, and other GenAI use cases like copilots, document intelligence, and knowledge assistants.
• Collaborate with product, engineering, and infrastructure teams to ensure seamless AI/ML system integration into scalable, secure cloud-native environments (AWS preferred).
• Establish and maintain robust MLOps pipelines using tools such as GitLab CI/CD, Docker, K8s
• Define best practices for model evaluation, benchmarking, and governance
• Manage, mentor, and grow a cross-functional team while fostering a culture of innovation, experimentation, and continuous learning in AI/ML.

Skills, Experience and Requirements
 

• Minimum 14 years of experience with 8+ years of experience in data science, machine learning, or AI, and at least 2+ years in a leadership or managerial role.
• Proven track record of delivering production-grade ML/GenAI systems at scale within enterprise environments.
• Strong expertise in Python ML frameworks
• Hands-on experience with LLMs, prompt engg, vector stores, RAG, agentic architecture 
• Deep understanding of Classical ML and Deep learning, NLP, GenAI
• Experience with AWS services: SageMaker, Lambda, S3, EKS, Athena, Bedrock
• Familiarity with software engineering practices including CI/CD, version control (Git), containerization (Docker), and orchestration (Kubernetes).
• Strong interpersonal, stakeholder management, and cross-functional collaboration skills.
• Prior experience applying Agile methodologies in AI/ML product development.
• Experience designing fully automated, configuration driven, extensible solutions
• Experience engaging in programs with multiple stakeholder organizations