AI Architect - Data Science

Job Description

Role Overview :As an AI Architect, you will be at the forefront of designing, developing, and implementing cutting-edge Artificial Intelligence and Machine Learning solutions that drive significant business impact. You will lead the architectural vision for our AI initiatives, translating complex business challenges into robust, scalable, and high-performance technical designs. This role involves close collaboration with cross-functional teams including data scientists, ML engineers, product managers, and business stakeholders, ensuring seamless integration and deployment of AI models into production environments. Your expertise will directly influence our product roadmap, enhance user experiences, and unlock new capabilities, positioning our organization as a leader in AI innovation. You will be instrumental in shaping the future of our intelligent systems, delivering tangible value to our customers and the business.Key Responsibilities :- Lead the architectural design and implementation of end-to-end AI/ML systems, ensuring solutions are scalable, reliable, and meet stringent performance requirements for various business applications.- Provide expert technical leadership and mentorship to engineering teams, fostering a culture of innovation, best practices, and continuous learning in AI/ML development.- Define and evolve the technical roadmap for AI initiatives, proactively evaluating emerging technologies such as Generative AI and advanced Prompt Engineering techniques to maintain a competitive edge.- Oversee the development and optimization of robust data pipelines, leveraging technologies like Spark, to ensure efficient data ingestion, processing, and feature engineering for ML model training and deployment.- Collaborate strategically with product, business, and data science teams to translate intricate business requirements into precise technical specifications and deliver impactful, data-driven solutions.- Establish and enforce architectural standards, MLOps best practices, and governance frameworks to ensure the integrity, security, and responsible deployment of AI models across the organization.Required Skillset:- Demonstrated deep expertise in Artificial Intelligence, Machine Learning, and Deep Learning principles, algorithms, and their practical application in enterprise environments.- Proven track record of designing and implementing large-scale, production-grade AI/ML systems with a focus on scalability, performance, and maintainability.- Strong proficiency in Generative AI models, including foundational models, and extensive experience with Prompt Engineering techniques for optimizing model outputs.- Extensive experience with big data technologies, particularly Apache Spark, for distributed data processing, ETL, and machine learning workflows.- Solid understanding of Data Science methodologies, statistical modeling, experimental design, and the ability to interpret complex analytical results.- Expertise in building and optimizing robust Data Pipelines, ensuring data quality, lineage, and availability for various AI/ML applications.- Proficiency in cloud platforms (AWS, Azure, GCP) and hands-on experience with MLOps practices for continuous integration, deployment, and monitoring of AI models.- Exceptional leadership and mentorship capabilities, with a proven ability to guide and inspire high-performing technical teams.- Excellent communication skills, both written and verbal, to articulate complex technical concepts and architectural decisions to diverse audiences, including senior leadership and non-technical stakeholders.- Strong problem-solving acumen, strategic thinking, and the ability to navigate ambiguous challenges in a fast-paced, dynamic environment.- Masters or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field from a premier institution.- At least 12-14 years of progressive experience in AI/ML architecture, engineering leadership, and solution delivery roles. .

Keyskills :
Artificial IntelligenceMachine LearningDeep LearningApache SparkData ScienceStatistical ModelingETLGenerative AIPrompt Engineering