Overview

Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future.

Responsibilities

• Leverage advanced analytics, ETL techniques, and visualization tools such as Tableau to deliver insights in a productized delivery model
• Work under the guidance of a Project Leader or Manager, contributing to strategy development and capability building
• Collaborate with case teams across geographies and industries, focusing exclusively on Commercial Excellence projects
• Independently manage workstreams within broader consulting engagements
• Provide technical expertise and innovative solutions to internal teams
• Collaborate with Project Leaders on data operations, analytics, and product development
• Perform data processing and statistical analysis using tools such as Alteryx, Python.
• Identify and integrate new data sources, analytical methodologies, and database management techniques
• Conduct data-driven storytelling, identifying key insights and customer segmentation
• Ensure accuracy and efficiency in research, analysis, and deliverables
• Synthesize insights, formulate actionable recommendations, and communicate them effectively to internal and client teams
• Facilitate cross-team collaboration and knowledge-sharing on technical best practices
• http://www.bain.com/about/what-we-do/awards/index.aspx
• https://www.bain.com/about/diversity-inclusion/

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.
• 2-5 years of professional experience in AI engineering, AI, chatbot development, or Gen AI roles.
• Strong proficiency in Python and SQL for building applications and data transformations and good familiarity with software engineering best practices.
• Partner with different COE leadership and delivery teams to understand workflows, pain points, and value levers across consulting data operations.
• Identify and prioritize high-impact opportunities where Agentic AI can improve accuracy, efficiency, and scalability of processes and delivery
• Design Agentic AI architectures (agents, tools, orchestration, memory, guardrails) and build rapid GenAI prototypes to prove value, iterate quickly with users, and define clear success metrics and adoption criteria.
• Build and optimize grounding and structured retrieval patterns (e.g., RAG with vector search) to ensure responses are traceable to domain data and maintain factual accuracy.
• Work with engineering to productionize validated prototypes into reliable, secure, and scalable services.
• Develop robust application and data-layer logic using Python and SQL, including APIs, pipelines, automation workflows, and maintainable codebases.
• Implement model evaluation, monitoring, and performance tracking for deployed systems (quality, latency, cost, bias, and safety).
• Ensure responsible AI practices and guardrails are embedded in design, covering evaluation frameworks, bias mitigation, and ethical considerations.
• Use AI-assisted development tools to accelerate delivery while maintaining engineering rigor and quality standards.
• Contribute to reusable frameworks, patterns, and documentation to enable repeatable build-and-scale of AI solutions across use cases.
• Stay up to date on state-of-the-art generative models, LLM tooling, and best practices to continuously elevate solution quality and performance