AI Product Leader

Role

AI Product Leader

The ideal candidate should have a strong understanding of AI/ML engineering and geospatial technologies, along with the ability to translate business requirements into scalable products and lead multidisciplinary technology teams.

Responsibilities

1. AI/ML Technology Strategy and Productization:

• Define and execute the AI/ML technology roadmap in alignment with business priorities and product strategy.
• Drive the development, productization and commercialization of

  AI-powered geospatial solutions

  across Utilities, Mapping, Telecom and Sustainability.
• Identify opportunities to apply Machine Learning, Deep Learning, Generative AI and intelligent automation to solve business problems and enhance geospatial products and services.
• Lead the development of scalable, reusable AI/ML capabilities that improve operational efficiency, automate workflows and deliver differentiated technology solutions.

2. AI/ML Engineering and Computer Vision

• Lead the design and implementation of AI/ML solutions using computer vision, image processing, predictive analytics and deep learning techniques.
• Drive automated feature extraction, object detection, image classification and semantic segmentation using satellite, aerial, LiDAR and other geospatial datasets.
• Guide the selection, evaluation, optimization and deployment of suitable AI/ML models based on accuracy, scalability, performance and business requirements.
• Evaluate the application of LLMs, Retrieval-Augmented Generation (RAG) and AI agents/Agentic AI for intelligent workflows, data interpretation and process automation.

3. Geospatial AI and Solution Architecture

• Design and oversee end-to-end architectures integrating GIS platforms, geospatial data pipelines, AI/ML models, APIs and enterprise applications.
• Drive AI-enabled mapping, automated feature extraction, asset identification, network design and planning, and geospatial data validation.
• Lead the design and implementation of

  AI-enabled solutions for UN Migration

  , leveraging geospatial intelligence, spatial analytics and predictive modelling to support relevant business and operational requirements.
• Ensure solutions can process large-scale spatial datasets and support reliable, scalable and efficient production workflows.

4. Cloud, AI Platform Engineering and MLOps

• Lead the development of scalable AI/ML platforms and cloud-based solutions using Microsoft Azure and/or AWS.
• Establish engineering practices for model deployment, monitoring, versioning, performance evaluation and continuous improvement (MLOps).
• Guide the use of Python, PyTorch/TensorFlow, distributed processing frameworks and modern deployment technologies, as appropriate to the solution architecture.
• Ensure production solutions meet requirements for scalability, reliability, security, maintainability and cost efficiency.

5. Technical Leadership and Business Partnership

• Work closely with business leaders, product teams and clients to translate market needs into technical roadmaps, solution designs and product capabilities.
• Participate in client presentations, solution demonstrations, bids and RFPs, providing technical leadership and solution feasibility assessments.
• Build and mentor multidisciplinary teams comprising AI/ML engineers, data scientists, GIS specialists and solution architects.

6. Technology Governance and Innovation

• Establish standards for AI/ML development, model validation, responsible AI, data governance and technology security.
• Evaluate emerging technologies and identify opportunities to improve automation, productivity, solution quality and competitive differentiation.
• Promote reusable architecture, engineering best practices and continuous technology innovation.

Required technical expertise

• Strong understanding of Machine Learning, Deep Learning, Computer Vision and AI/ML product engineering.
• Experience with computer vision techniques such as object detection, image classification and semantic segmentation.
• Familiarity with geospatial AI applications, including satellite/aerial imagery analysis, LiDAR processing, automated feature extraction or GIS-based analytics.
• Working knowledge of Python and at least one major deep learning framework, such as PyTorch or TensorFlow.
• Experience with cloud-based AI/ML platforms, preferably Microsoft Azure and/or AWS.
• Understanding of MLOps, model deployment, monitoring and production AI lifecycle management.
• Knowledge of scalable data pipelines, APIs, distributed computing and cloud-native solution architecture.
• Exposure to Generative AI, LLMs, RAG or AI agents is desirable.

Skills and qualification

• Bachelors or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering or a related discipline.
• 12+ years of relevant technology/product development experience, with substantial exposure to AI/ML solutions and technical leadership.
• Proven experience taking AI/ML solutions from concept or prototype through production deployment and productization.
• Experience leading cross-functional engineering teams and managing technology roadmaps.
• Strong business communication, stakeholder management and client-facing capabilities.
• Willingness to travel within India and internationally.