Experience Level: 10+ years (with at least 2-3 years in AI/ML/GenAI)Primary Skill: Amazon Bedrock, AWSResponsibilities- AI & Solution Architecture: Design scalable, secure, and high-performance AI/ML architectures aligned with organizational goals. * Build reference architectures, solution blueprints, and reusable frameworks for AI workloads.Evaluate and select appropriate AI tools, technologies, and platforms.- Model Development & Deployment:& * Partner with data scientists and engineers to operationalize machine learning models at scale. * Design model training, validation, testing, deployment, and monitoring workflows. * Define and implement MLOps best practices, including CI/CD automation for AI systems.- Data Architecture & Integration:*Architect data pipelines and feature stores that support model training and real-time inference. * Ensure high-quality data ingestion, transformation, governance, and lineage tracking.Collaborate with data engineering teams to optimize data accessibility and performance.- Governance, Security & Compliance: * Establish AI governance principles, including responsible AI, model explainability, and auditability..Required Qualifications- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.- 7+ years of experience in architecture, software engineering, or AI/ML solution delivery.- Strong knowledge of machine learning principles, deep learning techniques, and generative AI.- Hands-on experience designing and deploying AI systems in cloud or hybrid environments.- Proficiency in Python or similar languages used in AI/ML development.- Deep understanding of data architectures, APIs, microservices, and distributed systems.Preferred Qualifications- Experience with cloud-native AI services (e.g., model hosting, autoML, vector search, GPU workloads).- Familiarity with MLOps tools (MLflow, Kubeflow, SageMaker Pipelines, Azure ML Pipelines, etc.).- Experience with LLM architectures, RAG pipelines, and production-grade GenAI implementations.- Certifications in AI, cloud architecture, or data engineering.