About the Role: We are seeking an experienced AI Solutions Architect to join our Hyderabad office and lead the design, development, and deployment of scalable AI-driven solutions. You will collaborate with cross-functional teams to translate business requirements into technical architectures, ensure best practices in machine learning and cloud deployment, and guide stakeholders through the full project lifecycle from proof of concept to production. Responsibilities: Design end-to-end AI solution architectures that meet business objectives and performance requirements Lead technical evaluation and selection of machine learning frameworks, cloud services, and deployment tools Collaborate with data scientists, software engineers, and product managers to define requirements and deliverables Develop and enforce best practices for AI model development, versioning, testing, and deployment Architect and implement scalable cloud infrastructures on AWS, Azure, or GCP for model training and inference Define and implement CI/CD pipelines, containerization, and orchestration for AI workloads Conduct performance tuning, cost optimization, and security assessments of deployed solutions Mentor and guide engineering teams on AI, deep learning, and cloud architecture patterns Required Qualifications: 5–12 years of experience designing and delivering AI/ML solutions in enterprise environments Strong expertise in machine learning and deep learning frameworks (TensorFlow, PyTorch, scikit-learn) Proven experience architecting cloud solutions on AWS, Azure, or GCP Hands-on experience with AI model deployment, containerization (Docker), and orchestration (Kubernetes) Solid background in data science, feature engineering, and data pipeline design Proficiency in Python and relevant libraries for AI and data processing Deep understanding of software architecture principles, microservices, and API design Excellent communication skills to interact with technical and non-technical stakeholders Preferred Qualifications: Advanced degree (MS or PhD) in Computer Science, Engineering, or related field Certifications such as AWS Certified Solutions Architect, Google Professional Cloud Architect, or Microsoft Certified: Azure Solutions Architect Experience with MLOps tools (Kubeflow, MLflow, TFX) and monitoring frameworks Familiarity with big data technologies (Spark, Hadoop) and real-time streaming (Kafka) Experience leading cross-functional teams and mentoring junior engineers Knowledge of security best practices and compliance standards for AI applications