AI/ML Architect

Job Description We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization. You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities - Technical Leadership - Lead the technical design and architecture of complex Generative AI systems. - Ensure solutions align with business objectives, scalability requirements, and technical feasibility. - Guide development teams through best practices, architecture reviews, and technical decision-making processes. - Solution Architecture - Design and develop end-to-end Generative AI solutions, including data pipelines, model training, deployment, and real-time monitoring. - Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. - Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. - Design, train, and fine-tune AI/ML models, especially Generative AI and Large Language Models (LLMs), to address specific use cases. - Build conversational AI solutions and chatbots using frameworks such as LangChain, RAG (Retrieval-Augmented Generation), and Chain-of-Thought (COT) prompting. - Production Deployment - Lead the deployment of Generative AI models into production environments. - Optimize deployment pipelines leveraging tools like Docker, Kubernetes, and cloud-native services for orchestration. - Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. - Data Processing & Feature Engineering - Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. - Implement data wrangling, preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. - Optimize workflows to extract meaningful insights from large datasets. - Model Optimization - Identify and implement optimization strategies such as hyperparameter tuning, feature engineering, and model selection for performance enhancement. - Focus on computational efficiency and scaling models to production-level performance. - Pilot/POCs Development - Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. - Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. - Evangelization - Promote and drive the adoption of Generative AI solutions across customer and delivery teams. - Provide technical leadership and mentorship to teams working on GenAI projects. - Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. - Continuous Improvement - Stay at the forefront of AI advancements, frameworks, and tools, including emerging concepts in Generative AI. - Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications - 10+ years of experience in AI/ML architecture, model development, and production deployment. - Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions. - Hands-on experience with frameworks like LangChain, Retrieval-Augmented Generation (RAG), and advanced prompting techniques. - Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting. - Experience working with cloud platforms, primarily GCP, with optional experience in AWS or Azure. - Strong understanding of MLOps tools, pipelines, and model monitoring in production. - Proficiency in Python and SQL for model development and data processing. - Experience with data preprocessing, ETL workflows, and feature engineering for AI applications. - Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes. - Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions. - Experience working with large datasets for structured and unstructured AI applications. - Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies. - Proven track record of leading POCs/pilots and scaling them to production-grade deployments. Preferred Skills - Familiarity with Reinforcement Learning from Human Feedback (RLHF). - Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. - Strong understanding of orchestration for large-scale production environments. Key Attributes - Strong technical leadership and mentorship abilities. - Excellent communication and stakeholder management skills. - Strategic thinking with the ability to architect scalable and future-ready AI systems. - Passion for solving business challenges using state-of-the-art AI techniques. - Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us - Lead the development of cutting-edge Generative AI solutions for real-world applications. - Be part of a collaborative, innovative, and technology-driven team. - Opportunity to work with advanced AI/ML tools and frameworks. - Drive innovation through technical leadership, mentorship, and solution evangelization. - Continuous professional growth with access to the latest AI/ML technologies and frameworks.