Product Technical Supervisor

1 day ago

Chennai, Tamil Nadu, India beBeeLeadership Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Product Technical Lead

We are seeking an accomplished product technical supervisor to lead one of our key product teams within the ISA product group, focusing on Design Cost & Complexity.

Key Responsibilities:
  • Team Leadership and Management:
    • Directly manage and mentor a product team of approximately 10 individuals across various disciplines including Software Engineering, Data Science, Product Management, Design, and Technical Anchoring.
    • Foster a high-performing team culture, providing coaching, career development guidance, and performance management to optimize individual and team contributions.
    • Ensure the team is well-supported, identifying and addressing impediments to productivity and flow.
  • Technical Product Ownership and Delivery:
    • Provide hands-on technical leadership, guiding the team in architectural design, software development best practices, and the implementation of scalable, reliable, and performant cloud-native applications.
    • Oversee the entire product development lifecycle, from Proof-of-Concept (POC) to production-ready solutions, ensuring robust engineering and timely delivery.
    • Collaborate with Product Managers to translate business requirements into technical specifications, prioritize backlogs, and ensure delivered software aligns with desired business outcomes.
    • Champion code quality, participate in technical reviews, and ensure adherence to engineering standards and security protocols.
  • Software and Data Integration:
    • Partner closely with Data Scientist colleagues to integrate advanced analytics, machine learning models, and data-driven insights into product solutions.
    • Work with Data Factory teams to establish efficient data ingestion pipelines and support the creation of valuable data products.
    • Drive the exploration and implementation of emerging technologies such as Generative AI (Gen AI) and Large Language Models (LLMs) to enhance product capabilities and foster innovation.
    • Ensure MLOps principles are applied for the effective deployment and management of machine learning components within products.
  • Process Optimization and Collaboration:
    • Promote and enforce Agile software development methodologies, Product Development Organization (PDO) models, and DevSecOps practices (CI/CD, TDD, etc.) to maximize efficiency and quality.
    • Facilitate regular governance ceremonies, track flow metrics, and leverage data to inform decision-making and continuous improvement.
    • Identify and resolve technical blockers, manage dependencies, and orchestrate cross-functional collaboration across product groups and internal teams.
    • Build strong relationships with peer Product Line Managers, Data Science partners, and Chief Architects to identify emerging foundational product needs and drive cross-functional integration.

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