Architect

Candidate RequirementsEducation Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Experience 8–12+ years of experience in AI/ML engineering, data platforms, and cloud architecture. Minimum 4+ years of experience in AI/ML architecture, technical leadership, or solution architecture roles. Proven expertise in designing and implementing Generative AI (GenAI), Natural Language Processing (NLP), Large Language Model (LLM), and Agentic AI solutions. Strong experience in the US Healthcare domain, with deep knowledge of Revenue Cycle Management (RCM) platforms. Hands-on experience building multi-agent systems, autonomous AI solutions, and AI-driven automation platforms. Technical ExpertiseArtificial Intelligence & Machine Learning Agentic AI, autonomous systems, and multi-agent orchestration. Generative AI and LLM technologies, including Transformers, Hugging Face, LangChain, Retrieval-Augmented Generation (RAG), model fine-tuning, and prompt engineering. AI/ML frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn. Data Engineering & Analytics Big Data and streaming technologies, including Apache Spark, Hadoop, Amazon EMR, Amazon Redshift, Google BigQuery, Databricks, and Apache Kafka. Cloud & Platform Engineering Hands-on experience with AWS, Microsoft Azure, and Google Cloud Platform (GCP), including AI/ML services. Experience designing cloud-native, scalable AI platforms. Application Development Strong knowledge of .NET Core, RESTful APIs, microservices, and event-driven architectures. Experience with Robotic Process Automation (RPA) and enterprise automation platforms. DevOps & Infrastructure Experience with Kubernetes, Docker, DevOps practices, and CI/CD pipelines. Understanding of AI governance, security, privacy, and regulatory compliance frameworks. Core Competencies Strong architectural thinking with the ability to design scalable, enterprise-grade AI solutions. Ability to translate complex AI technologies into business-focused outcomes. Excellent executive communication, presentation, and stakeholder management skills. Proven leadership, mentoring, and cross-functional collaboration capabilities. Passion for building autonomous AI platforms and driving digital transformation in healthcare. Strategic Responsibilities Design and establish enterprise-scale AI/ML and Agentic AI platforms. Drive the adoption of autonomous, intelligent, and self-healing cloud operations. Position AI agents as core platform components within enterprise architecture. Lead the implementation of scalable, secure, compliant, and responsible Generative AI solutions across the organization.