AI/ML Architect

As a Technical Architect at Quadance Technologies Private Limited, your role will involve leading the design and development of scalable, enterprise-level applications and AI/ML solutions. You will be responsible for collaborating with stakeholders to translate requirements into maintainable architectures, implementing end-to-end solutions, providing technical leadership to development teams, and ensuring adherence to architectural standards. Additionally, you will participate in technical discussions with client teams, evaluate emerging technologies, and drive innovation in architecture and solutioning. Your key responsibilities will include: - Lead the architectural design and development of enterprise-level applications and AI/ML solutions. - Collaborate with business and technical stakeholders to translate requirements into scalable and maintainable architectures. - Design and implement end-to-end solutions focusing on performance, security, and maintainability. - Provide technical leadership and mentoring to development teams. - Conduct code reviews, enforce best practices, and ensure adherence to architectural standards. - Participate in technical discussions with client teams, providing guidance and strategic recommendations. - Oversee integration of AI/ML components, with a strong emphasis on RAG-based solutions. - Evaluate emerging technologies and drive innovation in architecture and solutioning. - Work closely with DevOps and QA teams to support CI/CD, automated testing, and deployment practices. To excel in this role, you should possess the following qualifications and skills: - 8-10 years of overall experience in software development and architecture. - Proven experience in designing and building large-scale enterprise applications. - Proficiency in either Python or C# .Net, with strong coding and debugging skills. - Solid understanding of architectural patterns such as microservices, event-driven, and layered architecture. - Hands-on experience with cloud platforms like AWS, Azure, or GCP. - Strong experience working with databases, APIs, and integration patterns. - Exposure to AI/ML solutions, particularly RAG-based architectures. - Familiarity with vector databases like FAISS, Pinecone, or Weaviate. - Strong understanding of LLMs, embeddings, prompt engineering, and data pipelines. - Excellent communication and interpersonal skills. - Experience interacting with client stakeholders in technical discussions. - Ability to manage technical teams, assign tasks, and ensure high-quality deliverables. Preferred qualifications include experience with containerization, exposure to MLOps, deployment of AI models in production, familiarity with Agile/Scrum methodologies, and certifications in cloud architecture or AI/ML.,