Large Language Model Architect

Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Large Language Models
Good to have skills : NA
Minimum 12 year(s) of experience is required
Educational Qualification : 15 years full time education
SUMMARY: We are seeking a Senior Technical – GenAI Lead with deep expertise in Python, AI/ML concepts, and data engineering to spearhead the design and development of Data Agents powered by Agentic AI. As a senior technical leader, you will drive solution architecture, guide teams, and ensure the successful delivery of AI-enabled initiatives that align with business goals. The ideal AI Lead combines technical excellence, leadership ability, prompt engineering skills, and a strong product mindset to ensure solutions are impactful, scalable, and business-driven. ROLES AND RESPONSIBILITIES: 1. Solution Architecture & Delivery • Lead the design, architecture, and implementation of AI-enabled solutions powered by Agentic AI. • Ensure scalability, reliability, and alignment of solutions with business objectives. 2. Team Leadership & Guidance • Mentor and guide cross-functional teams in AI/ML, data engineering, and product development. • Foster a collaborative environment that drives innovation and high-quality delivery. 3. AI/ML & Data Engineering Expertise • Spearhead the development of intelligent Data Agents leveraging Python, AI/ML models, and scalable data pipelines. • Apply advanced prompt engineering techniques to optimize the performance of LLMs and agentic workflows. 4. Collaboration & Stakeholder Engagement • Work closely with product managers, data scientists, and engineering teams to define AI-driven use cases. • Translate business goals into technical requirements and actionable AI solutions. 5. Innovation & Emerging Technologies • Stay ahead of trends in GenAI, Agentic AI, ML, and autonomous systems. • Introduce best practices, frameworks, and tools to enhance solution effectiveness and maintain competitive advantage. 6. Business-Driven Mindset • Align AI solutions with organizational strategy to maximize impact and business value. • Ensure delivered solutions are scalable, secure, and capable of driving measurable business outcomes. TECHNICAL EXPERIENCE: • Min 10 years of professional experience in the required skills - having min 2 year of GenAI experience • Lead the design and development of Data Agents leveraging Agentic AI principles, Python, and AI/ML frameworks. • Strong expertise in Python and PySpark for large-scale data engineering. • Solid foundation in AI/ML concepts (e.g., supervised/unsupervised learning, reinforcement learning, LLMs). • Experience architecting and deploying AI-driven solutions in production environments. • Proven leadership skills in managing teams, mentoring talent, and leading technical delivery. • Strong prompt engineering skills to refine LLM interactions and improve system outcomes. • Excellent communication and stakeholder management skills, with the ability to bridge business and technology. • Product mindset with a focus on usability, scalability, and delivering business impact. • Growth mindset and adaptability to thrive in an evolving digital and AI landscape • Define and own the technical architecture for scalable, secure, and efficient agent driven systems. • Apply prompt engineering techniques to optimize LLM performance and enhance agent effectiveness. • Guide and mentor analysts and developers in Python, PySpark, AI/ML best practices, and agentic system design. • Partner with product managers, data scientists, and business stakeholders to translate requirements into AI-driven solutions. • Drive a product-oriented approach, ensuring AI agents deliver measurable value aligned with business outcomes. • Ensure code quality, performance optimization, and adherence to engineering best practices. • Stay ahead of emerging trends in Agentic AI, LLMs, and autonomous systems to bring innovation into practice. • Lead proofs-of-concept (POCs) and enterprise-scale implementations of AI-based automation. ADDITIONAL ATTRIBUTES: • • Hands-on experience with LLM frameworks (e.g., LangChain, LlamaIndex) and Agentic AI orchestration tools. • • Familiarity with cloud AI/ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI). • Exposure to data governance, security, and compliance practices in enterprise AI systems. • • Experience with visualization and reporting tools to support data-driven decision making. EDUCATION QUALIFICATIONS: • A 15-year full-time education is required.