Job Description

Role Purpose

The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction.
 

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We are seeking a Principal Scientist – Generative AI & NLP to lead our research and development efforts in cutting-edge AI technologies, including Large Language Models (LLMs), multimodal AI, and agentic systems. This role is ideal for a seasoned AI researcher and technologist with a strong publication record, deep algorithmic expertise, and hands-on experience in building and optimizing large-scale AI systems under real-world constraints. You will play a pivotal role in setting the research direction, leading high-impact publications, and driving the development of scalable, production-ready AI solutions that power next-generation products.

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  • Provides technical and strategic input during the project planning phase in the form of technical architectural designs and recommendation
  • Collaborates with all relevant parties in order to review the objectives and constraints of solutions and determine conformance with the Enterprise Architecture
  •  Identifies implementation risks and potential impacts
• Enable Delivery Teams by providing optimal delivery solutions/ frameworks
  • Build and maintain relationships with executives, technical leaders, product owners, peer architects and other stakeholders to become a trusted advisor
  • Develops and establishes relevant technical, business process and overall support metrics (KPI/SLA) to drive results
  • Manages multiple projects and accurately reports the status of all major assignments while adhering to all project management standards
  • Identify technical, process, structural risks and prepare a risk mitigation plan for all the projects
  • Ensure quality assurance of all the architecture or design decisions and provides technical mitigation support to the delivery teams
  • Recommend tools for reuse, automation for improved productivity and reduced cycle times
  • Leads the development and maintenance of enterprise framework and related artefacts
  • Develops trust and builds effective working relationships through respectful, collaborative engagement across individual product teams
  • Ensures architecture principles and standards are consistently applied to all the projects
  • Ensure optimal Client Engagement
    • Support pre-sales team while presenting the entire solution design and its principles to the client
    • Negotiate, manage and coordinate with the client teams to ensure all requirements are met and create an impact of solution proposed
    • Demonstrate thought leadership with strong technical capability in front of the client to win the confidence and act as a trusted advisor

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• Mentorship & Collaboration

• Mentor junior scientists / engineers in GenAI best practices and research methodologies.
• Work cross-functionally to align AI initiatives with business goals and customer needs.

Required Qualifications

• Ph.D. or Master’s in Computer Science, Machine Learning, Mathematics, Computational Linguistics, or a related field.
• 10–15 years of industry and/or academic experience in AI/ML, with 7+ years in NLP and Generative AI.
• Demonstrated leadership in publishing top-tier research such as NeruralIPS, ICLR, ICML, AAAI, and CVPR in LLMs, multimodal models, or related areas.
• Proven experience in large-scale model training, optimization, and deployment.
• Expertise in Python, with proficiency in frameworks such as Hugging Face Transformers, TensorFlow, PyTorch, Keras, JAX.
• Deep understanding of LLMs, multimodal AI, embedding models, vector databases, and agentic AI.
• Experience with MLOps/LLMOps tools (e.g., MLflow, Weights & Biases, DVC, SageMaker, Vertex AI).
• Strong system design skills, including distributed systems, data pipelines, and API development.

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• Team Management 

  • Resourcing

    • Anticipating new talent requirements as per the market/ industry trends or client requirements
    • Hire adequate and right resources for the team 
  • Talent Management
    • Ensure adequate onboarding and training for the team members to enhance capability & effectiveness
    • Build an internal talent pool and ensure their career progression within the organization
    • Manage team attrition 
    • Drive diversity in leadership positions
  • Performance Management
    • Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports
    • Ensure that the Performance Nxt is followed for the entire team
  • Employee Satisfaction and Engagement
    • Lead and drive engagement initiatives for the team
    • Track team satisfaction scores and identify initiatives to build engagement within the team