R&D Senior AI Cloud Solutions

Senior R&D AI & Cloud Solutions Architect Position Overview We are looking for a highly skilled and innovation-driven Senior R&D AI & Cloud Solutions Architect to lead the research, design, development, and implementation of next-generation AI and cloud solutions. The role will focus on identifying emerging technologies, building AI-powered products and platforms, developing proof-of-concepts, and converting innovative ideas into scalable enterprise solutions. The ideal candidate will have strong hands-on experience across Artificial Intelligence, Generative AI, Machine Learning, Cloud Architecture, APIs, Data Platforms, and DevOps, combined with the ability to work in an R&D environment and translate business problems into technology solutions. Key Responsibilities AI & Generative AI R&D Research and evaluate emerging AI, Generative AI, LLM, NLP, computer vision, and intelligent automation technologies.Design and develop AI/ML and GenAI-based solutions for enterprise use cases.Develop and evaluate LLM applications, AI agents, RAG architectures, vector databases, prompt engineering, and model orchestration.Evaluate commercial and open-source AI models and frameworks.Build rapid prototypes and Proofs of Concept (PoCs) to validate new AI capabilities.Assess model performance, accuracy, scalability, security, and cost.Explore opportunities to integrate AI into existing enterprise applications and workflows. Cloud Architecture & Engineering Design scalable, secure, resilient, and cost-effective cloud architectures across AWS, Microsoft Azure, and/or Google Cloud Platform.Develop cloud-native AI and data solutions using services such as compute, containers, serverless, databases, storage, networking, and managed AI/ML platforms.Design hybrid and multi-cloud solutions where required.Establish cloud architecture standards, reference architectures, and technology patterns.Ensure solutions comply with enterprise security, governance, availability, and data protection requirements. R&D and Innovation Identify emerging technologies and assess their potential business value.Lead technology experiments, prototypes, technical evaluations, and innovation initiatives.Conduct technology/vendor evaluations and recommend appropriate platforms and frameworks.Maintain a technology roadmap covering AI, cloud, automation, data, and emerging technologies.Convert successful PoCs into production-ready solutions in collaboration with engineering and product teams.Stay current with developments in AI, cloud computing, cybersecurity, data engineering, and software architecture.Solution Development Work closely with business stakeholders, product teams, architects, developers, data scientists, and infrastructure teams.Translate business requirements into technical architecture and solution designs.Develop APIs, microservices, AI services, integrations, and cloud applications.Establish development standards for AI and cloud solutions.Ensure solutions are scalable, maintainable, observable, and production-ready.Support troubleshooting and optimization of AI/cloud solutions. MLOps / DevOps Implement CI/CD pipelines for AI and cloud applications.Establish MLOps practices covering model development, deployment, monitoring, versioning, and lifecycle management.Implement Infrastructure as Code using technologies such as Terraform, CloudFormation, or Bicep.Work with containerization and orchestration technologies such as Docker and Kubernetes.Implement monitoring, logging, performance management, and cost optimization. AI Governance & Security Incorporate responsible AI principles into solution design.Address data privacy, model security, access control, auditability, and AI governance requirements.Evaluate risks associated with GenAI, including hallucination, prompt injection, data leakage, model misuse, and unauthorized access.Develop appropriate guardrails and validation mechanisms for enterprise AI solutions. Required Technical Skills Artificial Intelligence / GenAI Generative AI and Large Language ModelsOpenAI / Azure OpenAI or equivalent LLM platformsRAG and vector searchPrompt engineeringAI agents and agentic workflowsNLP and Machine Learning fundamentalsPythonAI frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalentVector databases such as Pinecone, Weaviate, Milvus, or Azure AI Search Cloud Strong experience with one or more: Microsoft AzureAmazon Web Services (AWS)Google Cloud Platform (GCP) Preferred exposure to: Azure OpenAI / Azure AI FoundryAWS BedrockAmazon SageMakerGoogle Vertex AICloud Functions / Lambda / Azure FunctionsKubernetesDocker Software Engineering Python and/or JavaREST APIs and microservicesSQL and NoSQL databasesGit and GitHub/GitLab/Azure DevOpsCI/CDAgile/Scrum methodologiesAPI gateways and integration platforms Data & Analytics Data engineering conceptsData pipelines and ETL/ELTData lakes and data warehousesSQLReal-time data .