Job description
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 (LLMs)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
SUMMARY:
We are seeking a Senior Technical – Gen AI 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 Gen AI, 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 7 years of professional experience in the required skills - having min 2 years of Gen AI experience Lead the design and development of Data Agents leveraging Agentic AI principles, Python, and AI/ML frameworks. Strong expertise in Python and Py Spark 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, Py Spark, 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., Lang Chain, Llama Index) 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
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