Associate

The Commercial Excellence Coro Center of Excellence (CoE), situated within BCN, is a specialized unit focused on driving B2B growth through advanced analytics, scalable data operations, visualization, and intelligent automation. Fully integrated with Coro, Bain’s software and data business under the Commercial Excellence Practice, the CoE collaborates closely with Coro leadership and consulting teams to implement data-intensive solutions like MoneyMap and Profit Cube. Our team possesses extensive expertise in Alteryx, Tableau, Python, and advanced analytics/ML, delivering actionable insights and tangible client impact. Furthermore, the CoE features an in-house innovation hub dedicated to developing cutting-edge tools and products by leveraging GenAI and automation for enhanced speed, intelligence, and scalability.

About You:

• Associate: For candidates with undergraduate studies, 2-5 years of hands-on experience in AI/ML engineering, software engineering, or related roles building and deploying AI/GenAI. For postgraduate degree holders, 0-3 years of relevant experience.
• Senior Associate: For candidates with undergraduate studies, 5-8 years of hands-on experience in AI/ML engineering, software engineering, or related roles building and deploying AI/GenAI. For postgraduate degree holders, 3-6 years of relevant experience.
• Possess expert proficiency in Python and a strong command of SQL for application development and data transformations; demonstrate familiarity with software engineering best practices.
• Exhibit hands-on experience with agentic/AI orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
• Have experience working with leading LLM providers and APIs like OpenAI and Anthropic, with the ability to evaluate and integrate model offerings into practical workflows.
• Demonstrate a deep understanding of prompt engineering, RAG architectures, vector databases/embeddings, tool-calling, and function orchestration for building grounded and scalable AI applications.
• Possess experience designing and building scalable backend services and RESTful APIs that support GenAI/agent workflows.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and experience deploying AI systems in production is advantageous.
• Experience with containerization and CI/CD pipelines (e.g., Docker, Kubernetes, Jenkins/GitHub Actions) and secure deployment practices is a plus.
• Have practical experience with model evaluation, monitoring frameworks, and performance optimization to ensure reliability, cost efficiency, and responsible AI practices.
• Exhibit strong problem-solving and analytical abilities, with a proven track record of applying AI/GenAI technologies to address real business challenges.

What You’ll Do:

• Collaborate with Coro leadership and delivery teams to understand workflows, identify pain points, and define value levers within consulting data operations.
• Identify and prioritize opportunities where Agentic AI can significantly enhance the accuracy, efficiency, and scalability of processes and delivery.
• Design Agentic AI architectures, including agents, tools, orchestration, memory, and guardrails, and develop rapid GenAI prototypes to demonstrate value, facilitate user iteration, and establish clear success metrics and adoption criteria.
• Build and optimize grounding and structured retrieval patterns, such as RAG with vector search, to ensure responses are traceable to domain data and maintain factual accuracy.
• Work with engineering teams to transition validated prototypes into reliable, secure, and scalable production services, integrated with Coro platforms and enterprise data sources.
• Develop robust application and data-layer logic using Python and SQL, encompassing APIs, pipelines, automation workflows, and maintainable codebases.
• Implement model evaluation, monitoring, and performance tracking for deployed systems, considering quality, latency, cost, bias, and safety.
• Ensure responsible AI practices and guardrails are integrated into the design process, including evaluation frameworks, bias mitigation strategies, and ethical considerations.
• Utilize AI-assisted development tools to accelerate delivery while upholding engineering rigor and quality standards.
• Contribute to the development of reusable frameworks, patterns, and documentation to enable repeatable build-and-scale approaches for AI solutions across various use cases.
• Stay current with state-of-the-art generative models, LLM tooling, and best practices to continuously improve solution quality and performance.