AI Platform Architect

Key Responsibilities - Architect and design end-to-end LLM-based systems, including Retrieval-Augmented Generation (RAG) and agentic workflows. - Define and implement system design patterns to ensure scalability, low-latency inference, and high-throughput workloads. - Lead architectural decisions regarding model selection, retrieval strategies, and orchestration frameworks. - Design and build enterprise-grade LLM platforms to enable rapid experimentation and standardized deployment. - Establish best practices for CI/CD in ML & LLM systems, including model/version lifecycle management and evaluation frameworks. - Drive the development of enterprise copilots, decision intelligence systems, and automation agents. - Mentor and build a high-performing team of AI, ML, and platform engineers while fostering a culture of innovation and engineering excellence. - Ensure compliance with security standards and implement governance frameworks for model evaluation and auditability. Overview - The LLM Ops AI Platform Architect is a pivotal role in our consulting sector, aimed at driving the design and development of cutting-edge AI platforms and LLM-powered systems. - Positioned in a hybrid work model across several major Indian cities, this role requires a blend of hands-on architecture and leadership skills to build innovative AI systems beyond traditional MLOps. - This position involves architecting next-generation AI capabilities such as RAG systems, agentic workflows, and enterprise copilots, ensuring scalability, security, and production-readiness. - The role is critical for translating business problems into scalable AI solutions and involves significant collaboration across product, business, and data teams. - Candidates will engage in high-level architectural decisions and lead the development of AI systems while fostering a culture of innovation and engineering excellence within the team. - The role provides a unique opportunity to work with emerging tools and frameworks in generative AI and offers high visibility and ownership across the organization. - The ideal candidate will have extensive experience in AI/ML, particularly with LLMs and Generative AI, and will be instrumental in shaping the future of enterprise AI platforms. - This position not only involves building and mentoring a high-performing team of AI, ML, and platform engineers but also emphasizes the importance of responsible AI practices, security, and governance. - As a senior member of the team, the platform architect will ensure compliance with enterprise-grade security standards and establish governance frameworks for model evaluation, explainability, and auditability. - The role is suited for professionals with a strong background in AI/ML, cloud platforms, and a deep understanding of scalable system design and MLOps/LLMOps practices. - Candidates with a passion for innovation and a desire to work on enterprise-scale AI platforms will find this position highly rewarding. Requirements - 8+ years of experience in AI/ML with a focus on LLMs and Generative AI. - Proven experience in designing and deploying production-grade AI systems. - Strong programming skills in Python and experience with cloud platforms such as AWS, Azure, or GCP. - Hands-on experience with RAG pipelines and vector databases such as FAISS, Pinecone, or Milvus. - Deep understanding of MLOps/LLMOps practices and containerization with Docker and Kubernetes. - Experience with agentic frameworks like LangChain, LangGraph, or AutoGen. - Familiarity with LLM evaluation frameworks and experience in enterprise AI governance.