BCG has 54 active AI-related job listings. The application stage dominates these openings, accounting for 69% of roles, followed by the agents stage at 28%. Engineering is the top function, and the company is hiring in India, the United States, and France. Frequent tech tags include agent_orchestration, rag, and llm_observability, suggesting a focus on agent-based AI systems and their operational aspects. Over the last 30 days, BCG has posted 40 new AI roles, representing a 21% increase compared to the previous 30-day period.
Currently tracking 36 active AI roles, down 66% versus the prior 4 weeks. Primary focus: Ship · Engineering. Salary range $137k–$143k (avg $140k).
BCG currently has 18 active AI-related roles in our index. The most common open titles are: (Senior) Forward Deployed AI Scientist, Greater China - BCG X, AI Architect (all genders) - BCG Platinion Vienna, Austria, AI Architect (all genders) - BCG Platinion Zurich, Switzerland, BCG Platinion | Principal Architect - AI Platforms, Data Analyst, Predictive Analytics, India- X Delivery. Most positions are in Engineering.
BCG's active AI hiring is concentrated in: application (50%), agents (33%), data (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
BCG is hiring AI talent in: India (4 roles), Thailand (2 roles), Netherlands (2 roles), United States (1 role).
Job postings at BCG most frequently reference: model serving, agent orchestration, inference infra, llm observability, rag.
In the past 30 days, BCG has posted 13 new AI-related roles. That is a -75% change versus the prior 30 days (51 → 13).
| Title | Stage | AI score |
|---|---|---|
| AI Architect (all genders) - BCG Platinion Vienna, Austria The role focuses on designing and developing AI-driven architectures, agentic platforms, and autonomous delivery pipelines for enterprise clients. This involves creating AI-powered software factories, implementing governance and security mechanisms for AI systems, and translating enterprise knowledge into machine-readable structures for autonomous development. The position requires hands-on experience with AI systems like LLMs and AI agents, and familiarity with modern software delivery approaches. | Agent | 7 |