Associate - AI Engineer (CTE)

Bain & Company; New Delhi; On-site; INR 1,000,000 - 1,600,000; Full time

Job summary

Bain & Company is seeking an AI Engineer with 2-5 years of experience in AI, chatbot development, or Gen AI roles to join our Delhi team. You will design agentic AI architectures, build GenAI prototypes, and work with delivery teams to identify high-impact opportunities for improved accuracy and scalability.

You will also work on grounding and retrieval patterns to ensure factual accuracy, productionize prototypes, and develop robust data-layer logic with Python and SQL while adhering to

Qualifications

• Bachelor’s degree in CS/Engineering/IS or related field required.
• 2–5 years of professional AI engineering, AI, chatbot development, or Gen AI roles.
• Strong proficiency in Python and SQL for building applications and data transformations.

Responsibilities

• Leverage advanced analytics, ETL techniques, and visualization tools to deliver insights in a productized delivery model.
• Collaborate with COE leadership and delivery teams to understand workflows and value levers.
• Design Agentic AI architectures and build rapid GenAI prototypes to prove value.

Skills

Analytical thinking

Communication

Collaboration

Problem solving

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Tools

Python

SQL

Tableau

Alteryx

APIs

Job description

About you

• 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

What you’ll do

1. Leverage advanced analytics, ETL techniques, and visualization tools such as Tableau to deliver insights in a productized delivery model
2. Work under the guidance of a Project Leader or Manager, contributing to strategy development and capability building
3. Collaborate with case teams across geographies and industries, focusing exclusively on Commercial Excellence projects
4. Independently manage workstreams within broader consulting engagements
5. Provide technical expertise and innovative solutions to internal teams
6. Collaborate with Project Leaders on data operations, analytics, and product development
7. Perform data processing and statistical analysis using tools such as Alteryx, Python.
8. Identify and integrate new data sources, analytical methodologies, and database management techniques
9. Conduct data-driven storytelling, identifying key insights and customer segmentation
10. Ensure accuracy and efficiency in research, analysis, and deliverables
11. Synthesize insights, formulate actionable recommendations, and communicate them effectively to internal and client teams
12. Facilitate cross-team collaboration and knowledge-sharing on technical best practices