Architect

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 domain experience in the U.S. Healthcare industry, with a focus on Revenue Cycle Management (RCM) platforms. Hands-on experience building multi-agent systems, autonomous AI solutions, and AI-driven automation platforms. Technical SkillsAI & 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 Platforms Hands-on experience with AWS, Microsoft Azure, and Google Cloud Platform (GCP), including AI/ML services. Application Development Experience developing APIs and microservices using .NET Core, RESTful APIs, and event-driven architectures. Automation & DevOps Experience with Robotic Process Automation (RPA) and intelligent automation platforms. Proficiency in DevOps practices, CI/CD pipelines, Kubernetes, and Docker. Governance & Security Strong understanding of AI governance, security, compliance frameworks, and responsible AI best practices.