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. Show more Show less
