Join BCG Platinion as a Lead AI Tech Architect, driving the design and implementation of cutting-edge AI platforms and agentic systems. This role blends platform architecture expertise with hands-on technical leadership, focusing on creating scalable AI solutions that integrate Large Language Models (LLMs), data pipelines, and enterprise systems. You will be instrumental in shaping the future of AI-driven products and capabilities.

BCG Platinion, part of BCG's Tech and Digital Advantage practice, empowers clients with innovative technology solutions. We bridge the gap between strategic vision and pragmatic execution, transforming businesses and revolutionizing approaches through deep expertise in Architecture, Cybersecurity, Digital Transformation, and more. Our global presence and commitment to digital excellence enable clients to navigate complex challenges and achieve their digital aspirations.

Design robust AI and LLM-based system architectures, balancing scalability, performance, and operational complexity. Evaluate and recommend emerging AI frameworks and tooling for optimal fit. Architect agentic AI solutions for intelligent workflow automation, incorporating task decomposition, memory management, and orchestration patterns. Define integration patterns for RAG, model orchestration, prompt workflows, and enterprise system connectivity. Develop proof-of-concepts and prototypes to validate AI platform designs and agent orchestration. Support the transition of AI platforms from prototype to production, contributing to performance, observability, and governance strategies. Facilitate technical discussions, translate complex AI concepts for diverse stakeholders, and provide architectural guidance.

A Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field is required, with a Master’s degree being a plus. You should have 6+ years of experience in software engineering, data engineering, or AI systems, with a strong foundation in software architecture and distributed systems. Experience designing production-ready AI/ML or LLM-based systems is essential. Familiarity with modern AI agentic frameworks (e.g., LangChain, LangGraph, Semantic Kernel) and concepts like RAG, multi-agent orchestration, and memory patterns is crucial. A solid understanding of cloud architecture (AWS, Azure, or GCP), data platforms, and API-based system integration is necessary. Experience with containerization and orchestration technologies (Docker, Kubernetes) is beneficial. Strong analytical thinking, problem-solving skills, and the ability to explain technical concepts to both technical and non-technical audiences are vital. A consulting mindset, comfortable operating in ambiguous and fast-paced environments, is expected.