Lead, AI Engineering

Bain & Company's AI, Insights & Solutions team is hiring a hands-on AI engineering lead to build enterprise GenAI and agentic applications with consulting teams and clients. The work spans proofs of concept, MVPs and, where appropriate, production deployments, with growing influence on technical direction and an opportunity to begin mentoring junior colleagues.

Responsibilities

• Build LLM-powered copilots, workflow automation and decision-support applications. Design agentic workflows that use enterprise tools and data for multi-step tasks, with human-in-the-loop controls and attention to reliability, safety and failure modes.
• Develop search, retrieval and knowledge pipelines across vector, graph and traditional data stores. Address indexing, metadata, relevance and reranking, freshness, caching, access controls and source attribution; implement agent context, memory, orchestration and routing.
• Integrate applications with enterprise APIs and workflows while balancing quality, latency, cost, privacy and adoption. When useful, prepare data, engineer features, develop or integrate ML models, and create reproducible training and evaluation pipelines.
• Deliver testable AI services from development through deployment, monitoring and iteration. Apply MLOps and GenAIOps practices, build evaluation and observability, protect sensitive data, and create reusable components. Translate ambiguous client needs into delivery plans, communicate technical tradeoffs, and support proposal scoping and risk assessment.

Requirements

• 3–5+ years of professional AI/ML engineering experience, or equivalent, with strong backend engineering fundamentals. Proficiency in Python; experience with APIs, enterprise integration, LLM applications, advanced retrieval, agentic patterns and production engineering practices.
• Experience operating services on AWS, GCP and/or Azure, using Docker and Kubernetes or equivalent orchestration. Ability to address AI security, privacy and governance requirements.
• Experience training and evaluating ML models, preprocessing data and applying feature engineering; familiarity with classical ML, deep learning, PyTorch or TensorFlow, and ML lifecycle tooling. Strong communication, stakeholder management and ability to deliver in ambiguous client-facing settings.

Working arrangement: Based in Bengaluru, Mumbai or New Delhi. At least three days a week must be spent working together in person at a client location or Bain home office. Travel beyond the primary location is required and varies by project. Application deadline: 26 October 2026.