AI/ML Architect

Description : We are seeking a highly experienced AI Solutions Architect with deep expertise in Artificial Intelligence, Machine Learning, and Generative AI (GenAI). This role involves leading the design, development and deployment of scalable AI/ML solutions and tools with a strong focus on innovative architectures. The ideal candidate will collaborate across teams to deliver high-performance AI systems aligned with business objectives and future scalability.In this Role, Your Responsibilities Will Be : - Design and implement full-stack scalable AI/ML systems integrating frontend (React/Angular), backend (Python/Node.js), RESTful APIs, RAG and agentic frameworks (LangChain, AutoGen).- Architect distributed, microservice-based AI pipelines using event-driven architectures and containerized deployments on Azure and AWS (secondary).- Advanced ML/DL models including GPT, BERT, CNNs, RNNs, GANs for NLP, computer vision, and multimodal applications.- Engineer prompt-based systems using retrieval-augmented generation (RAG), few-shot learning, and prompt tuning to optimize LLM performance.- Lead data preprocessing workflows with Spark, Pandas, and MLFlow, including feature engineering and data augmentation.- Model observability frameworks for drift detection, performance monitoring, and lifecycle management using tools like Prometheus and Grafana.- Apply model optimization techniques such as quantization, pruning for real-time, low-latency inference.- Enforce AI/ML system security by integrating data protection protocols, implementing role-based access control (RBAC), encryption standards (TLS, AES), and ensuring compliance with regulatory frameworks such as GDPR, HIPAA, and ISO/IEC 27001 through automated policy enforcement and audit logging.- Ensure AI security, governance through bias mitigation, explainability and secure deployment aligned with compliance standards.- Conduct technical feasibility assessments, PoCs, and infrastructure cost estimation with risk analysis.- Lead AI architecture with cross-functional collaboration, Agile execution, and continuous innovation while maintaining technical excellence and comprehensive documentation.- Exceptional ability to articulate complex AI and technical concepts with clarity, enabling effective communication across technical and non-technical stakeholders.Qualifications : - Bachelor's or Masters degree in Computer Science, Data Science, or related field with 10+ years in AI/ML architecture and enterprise-grade solution delivery.- Over 5 years of specialized experience in architecting and deploying AI/ML systems, with a demonstrated history of delivering production-grade solutions across diverse use cases.- Hands-on experience with agentic frameworks (LangChain, AutoGen), prompt engineering, and scalable LLM deployment.- Strong expertise in GenAI, Machine Learning, Data Science, transformer models (GPT, BERT), deep learning (CNNs, RNNs, GANs), and multimodal AI systems.- Proficient in Python and ML/DL frameworks like TensorFlow, PyTorch, Hugging Face, and MLFlow.- Skilled in designing distributed AI pipelines using microservices, containerization (Docker, Kubernetes) and cloud platforms (Azure, AWS-secondary).- Deep understanding of data engineering, CI/CD automation, model observability, and performance optimization.- Specialized in AI security including adversarial robustness, federated learning, encryption standards, and regulatory compliance.- Proven leadership in Agile environments, technical mentoring, and translating business needs into scalable AI architectures.- Passionate about innovation with a track record of integrating emerging AI technologies into production-ready systems.Preferred Skills : - Proven experience in developing AI-powered solutions across industries.- Strong understanding of MLOps practices, CI/CD pipelines, and Azure DevOps for scalable AI deployment.- Solution Architect Certifications is plus advantage like AZ-305 : Azure Solutions Architect Expert, AWS Certified Solutions Architect.- Deep knowledge of secure and ethical AI design, including data privacy regulations and responsible AI principles.- Demonstrated success in leading GenAI/ML projects from concept to production with measurable impact.- Advanced problem-solving and analytical skills for translating complex challenges into efficient AI solutions.- Excellent communication and collaboration abilities to bridge technical and non-technical stakeholders- - - - - - - (ref:hirist.tech)