Director of Artificial Intelligence and Expertise

Lead – AI and GenAI

The Director of AI and GenAI will lead a team focused on the Lighthouse TM platform. This role provides architectural and algorithmic leadership to evolve AI and GenAI driven problem discovery, root cause analysis, and action recommendation modules within the platform to solve critical client problems at scale.

• Advanced AI and GenAI for Problem Discovery, RCA and Action Recommendation:
  • Lead data scientists, GenAI developers, and ML engineers in hands-on mode to develop and deploy advanced models based on long short-term memory, sequence learning, and retrieval augmented generation along with classical machine learning models, including anomaly detection, predictive analytics, causal inferencing, and action recommendation models.
  • Develop pipelines that autonomously discover problems, identify root causes, and recommend actions in real-time and batch processing scenarios while ensuring that models are interpretable, scalable, and optimized for performance in production environments at big data scale.
• Gen-AI-Powered Analysis and Insights Generation:
  • Lead data scientists in hands-on mode to create and fine-tune Generative AI models to assist in analysis creation for problem discovery, translating complex data patterns and root cause findings into actionable, natural language insights for stakeholders.
  • Implement prompt engineering and fine-tuning techniques to enhance the relevance and accuracy of insights.
• Reference Architectures:
  • Work with Technical Architects to evolve frameworks for augmenting and evolving batch processing data architectures with streaming architectures to support connected data and ML pipeline executions in real-time.
  • Adapt reference architectures that operationalize AI and Gen-AI models optimally in both batch and real-time modes.
• Client Deployments of the Platform:
  • Consult and provide guidance for creating automated data pipelines for raw data and engineered features ensuring data quality, integrity, and accessibility for model training and inference.
  • Help establish robust MLOps and LLMOps practices, including automated model monitoring, retraining triggers, and performance benchmarking, including assessment of model accuracy and drift parameters, and the business impact.
• Development of Use Cases:
  • Lead and support development of use cases on the platform for various vertical specific problem statements.
  • Support platform demonstration meetings by participating and leading discussions around explanation of platform capabilities and fitments.
• Leadership and Collaboration:
  • Lead and mentor a team of data scientists and machine learning engineers, providing guidance on best practices in GenAI, AI/ML methodologies, and coding standards.
  • Collaborate closely with product managers, data engineers, and business analysts to align AI solutions with platform goals and user requirements in accordance with the platform roadmap.
• Pre-sales:
  • Support pre-sales, marketing hyper-scaler partnerships, and other sales activities such as RFPs by providing subject matter expertise during scoping and designing of the engagements.
  • Support the client development efforts by contributing to developing proposals, POVs, and other POC read-outs.

Skills & Qualifications

• In-depth conceptual understanding of Statistics, Classical Machine Learning, Deep Learning, and GenAI, along with significant hands-on development experience in these areas.
• Able to understand the nuances of business problems in various domains, quickly grasp the problem discovery analysis, and modelling imperatives, and translate those into the requirements for AI models.
• Significant exposure to various proprietary & open-source cloud-based Machine Learning platforms.
• Experience in leveraging open-source LLMs and prompt engineering, RAG based training, and SLM model development.
• Hands-on with excellent ML programming skills in Python using open-source libraries.
• Experience in working with RDBMS and NoSQL databases; Exposure to Big Data technologies.
• 12-18 years of Machine Learning model development and application experience.
• Experience in building cloud-based products that implement GenAI and ML modelling as a service.