Senior AI Solutions Architect

Job Summary: We are seeking an experienced Senior AI Architect with strong hands-on expertise in artificial intelligence, machine learning, solution architecture, and enterprise AI integration. The role involves designing, developing, and deploying scalable AI solutions integrated with enterprise platforms, data lakes, APIs, and business applications. The ideal candidate should have experience with AI frameworks and tools such as Hugging Face, LangChain, Microsoft Foundry, and OpenAI APIs, along with cloud technologies, data engineering, and enterprise system integration. Key Responsibilities: • Design, develop, and deploy scalable AI and machine learning solutions aligned with business requirements and enterprise architecture standards. • Build and implement AI-powered applications using frameworks and platforms such as Hugging Face, LangChain, Microsoft Foundry, and OpenAI APIs. • Develop and integrate AI solutions with enterprise platforms such as Salesforce CRM, data lakes, content management systems (CMS), APIs, and legacy applications. • Design and implement AI solution architectures, ensuring scalability, performance, reliability, and maintainability. • Apply machine learning algorithms, deep learning techniques, natural language processing (NLP), and other AI methodologies to solve complex business problems. • Develop and maintain data pipelines, ETL workflows, and data processing solutions to support AI and machine learning applications. • Integrate AI systems with enterprise applications and legacy platforms using RESTful APIs, middleware, and other integration technologies. • Work with cloud infrastructure and services, particularly Microsoft Azure, to develop, deploy, and manage AI solutions. • Implement containerized AI applications using Docker and Kubernetes, following DevOps and deployment best practices. • Establish and maintain architecture governance, coding standards, code quality, and technical best practices across AI development initiatives. • Ensure data security, privacy, compliance, and responsible AI practices throughout the AI solution lifecycle. • Collaborate with data scientists, data engineers, software developers, enterprise architects, and business stakeholders to deliver end-to-end AI solutions. • Evaluate emerging AI technologies, frameworks, and tools to identify opportunities for innovation and improve solution effectiveness. • Troubleshoot AI application, data pipeline, integration, and deployment issues to ensure reliable production operations. Role Requirements and Qualifications: • Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field. • 12–20 years of relevant experience in solution engineering, or solution architecture. • 6–8 years of relevant experience in AI, machine learning. • Proven experience designing, developing, and deploying AI and machine learning solutions in enterprise environments. • Strong programming skills in Python, Java, C++, or similar languages, with Python preferred for AI development. • Hands-on experience with AI frameworks and platforms such as Hugging Face, LangChain, Microsoft Foundry, and OpenAI APIs. • Strong understanding of machine learning algorithms, deep learning, data processing, and AI application development. • Experience designing AI solutions integrated with enterprise platforms such as Salesforce CRM, data lakes, CMS platforms, and APIs. • Hands-on experience with cloud platforms and services, particularly Microsoft Azure. • Familiarity with data pipeline tools, ETL processes, data engineering concepts, and data lakehouse platforms. • Experience with RESTful APIs, middleware, enterprise application integration, and legacy system integration. • Working knowledge of Docker, Kubernetes, containerization, and DevOps practices. • Strong understanding of data architecture, data science principles, and security and privacy considerations in AI systems. • Ability to drive architecture governance, code quality, technical standards, and scalable solution design. • Strong analytical, troubleshooting, problem-solving, and communication skills. Preferred Qualifications: • Experience with Microsoft Fabric and data lakehouse architectures. • Experience implementing advanced AI techniques, including reinforcement learning, natural language processing (NLP), and computer vision. • Knowledge of Generative AI, large language models (LLMs), Retrieval-Augmented Generation (RAG), and AI application development. • Familiarity with AI ethics, responsible AI practices, bias mitigation, and model governance. • Experience with cloud-based AI services, enterprise data platforms, and AI deployment automation. • Knowledge of CI/CD pipelines, infrastructure automation, and monitoring of AI applications in production. • Experience working in Agile/Scrum environments and collaborating across cross-functional teams. • Strong analytical thinking and problem-solving skills, with the ability to translate complex business problems into effective AI solutions. • Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to technical and non-technical stakeholders. • Leadership capabilities and the ability to guide technical decisions and collaborate effectively with cross-functional teams. • Detail-oriented, with a strong focus on delivering secure, high-quality, scalable, and maintainable solutions. • Innovative, proactive, and self-motivated, with a willingness to explore emerging AI technologies and drive continuous improvement. • Ability to work independently and collaboratively in a dynamic, fast-paced environment with changing business and technical requirements. Why Join Us: • Opportunities to work on transformative AI and Generative AI projects with leading global organizations. • Continuous investment in learning, upskilling, and professional development. • Collaborative work environment with experienced technology professionals. • Competitive compensation and comprehensive employee benefits. • A culture that encourages innovation, ownership, and career growth.

Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field. 12–20 years of relevant experience in solution engineering, or solution architecture. 6–8 years of relevant experience in AI, machine learning. Proven experience designing, developing, and deploying AI and machine learning solutions in enterprise environments. Strong programming skills in Python, Java, C++, or similar languages, with Python preferred for AI development. Hands-on experience with AI frameworks and platforms such as Hugging Face, LangChain, Microsoft Foundry, and OpenAI APIs. Strong understanding of machine learning algorithms, deep learning, data processing, and AI application development. Experience designing AI solutions integrated with enterprise platforms such as Salesforce CRM, data lakes, CMS platforms, and APIs. Hands-on experience with cloud platforms and services, particularly Microsoft Azure. Familiarity with data pipeline tools, ETL processes, data engineering concepts, and data lakehouse platforms. Experience with RESTful APIs, middleware, enterprise application integration, and legacy system integration. Working knowledge of Docker, Kubernetes, containerization, and DevOps practices. Strong understanding of data architecture, data science principles, and security and privacy considerations in AI systems. Ability to drive architecture governance, code quality, technical standards, and scalable solution design. Strong analytical, troubleshooting, problem-solving, and communication skills.

Design, develop, and deploy scalable AI and machine learning solutions aligned with business requirements and enterprise architecture standards. Build and implement AI-powered applications using frameworks and platforms such as Hugging Face, LangChain, Microsoft Foundry, and OpenAI APIs. Develop and integrate AI solutions with enterprise platforms such as Salesforce CRM, data lakes, content management systems (CMS), APIs, and legacy applications. Design and implement AI solution architectures, ensuring scalability, performance, reliability, and maintainability. Apply machine learning algorithms, deep learning techniques, natural language processing (NLP), and other AI methodologies to solve complex business problems. Develop and maintain data pipelines, ETL workflows, and data processing solutions to support AI and machine learning applications. Integrate AI systems with enterprise applications and legacy platforms using RESTful APIs, middleware, and other integration technologies. Work with cloud infrastructure and services, particularly Microsoft Azure, to develop, deploy, and manage AI solutions. Implement containerized AI applications using Docker and Kubernetes, following DevOps and deployment best practices. Establish and maintain architecture governance, coding standards, code quality, and technical best practices across AI development initiatives. Ensure data security, privacy, compliance, and responsible AI practices throughout the AI solution lifecycle. Collaborate with data scientists, data engineers, software developers, enterprise architects, and business stakeholders to deliver end-to-end AI solutions. Evaluate emerging AI technologies, frameworks, and tools to identify opportunities for innovation and improve solution effectiveness. Troubleshoot AI application, data pipeline, integration, and deployment issues to ensure reliable production operations.