Description & Requirements

About us

Bain & Company is a global management consulting firm that helps the world's most ambitious change makers define the future. Across 65 offices in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition and redefine industries. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry.

In 2004, the firm established its presence in the Indian market by opening the Bain Capability Center (BCC) in New Delhi. The BCC is now known as BCN (Bain Capability Network) with its nodes across various geographies. BCN is an integral and largest unit of (ECD) Expert Client Delivery. ECD plays a critical role as it adds value to Bain's case teams globally by supporting them with analytics and research solutioning across all industries, specific domains for corporate cases, client development, private equity diligence or Bain intellectual property. The BCN comprises of Consulting Services, Knowledge Services and Shared Services.

Who you will work with

BCN Private Equity Group CoE at Bain & Company provides specialized support to global teams across the private equity value chain, enabling clients to make key investment decisions. Our expertise lies in addressing critical diligence questions through a range of products such as survey analytics, digital diagnostic, workforce analytics and disruption assessment. Our teams work in a fast-paced environment delivering consistent and impactful results at scale. In the last decade, we have witnessed an exponential growth, reaching >250 members today from ~10 members in 2013. We operate from 3 locations - 2 in India and 1 in Poland, and operate across all 3 regions (EMEA, Americas and APAC). BCN PEG provides an opportunity to solve challenging business problems in a dynamic set-up working closely with global Bain teams, acting as a thought-partner with daily deliverables.

What you'll do

• Build and maintain data models, schemas, transformation layers, and reusable data components that support analytics and AI-enabled applications.
• Develop and integrate AI/LLM-based capabilities such as Retrieval-Augmented Generation (RAG), semantic search, information extraction, summarization, copilots, and agentic workflows.
• Build robust ingestion, transformation, validation, and enrichment pipelines to prepare enterprise data for analytics, machine learning, and GenAI use cases.
• Work with relational, NoSQL, analytical, and vector databases to support application, analytics, and AI workloads.
• Develop APIs, services, and reusable components that enable applications and AI systems to securely consume data and model capabilities.
• Implement retrieval pipelines using embeddings, vector search, metadata filtering, reranking, and other techniques to improve the relevance and quality of LLM-powered applications.
• Support the evaluation and monitoring of AI/LLM solutions using appropriate datasets and metrics to assess retrieval quality, response quality, latency, reliability, and cost.
• Apply software engineering best practices including modular design, automated testing, version control, documentation, code review, and CI/CD.
• Optimize data and AI workloads for performance, scalability, reliability, and cost across development and production environments.
• Implement appropriate data quality, access control, security, privacy, and governance practices in line with Bain's organizational policies and responsible AI standards.
• Collaborate with product managers, data scientists, software engineers, DevOps engineers, and business stakeholders to translate business requirements into scalable technical solutions.
• Troubleshoot data pipeline, application, retrieval, and model-integration issues and contribute to improving the observability and reliability of production systems.
• Contribute to shared data and AI platform components, common libraries, data contracts, APIs, and engineering standards that can be reused across PEG Alpha products.
• Evaluate emerging AI/LLM technologies and frameworks and contribute to technical decisions based on solution quality, scalability, security, maintainability, and cost.
• Use GenAI-assisted development tools (e.g., GitHub Copilot, Cursor or equivalent) responsibly to accelerate development, testing, debugging, and technical documentation while reviewing generated outputs against team engineering standards.
• Should be Familiar with Pyspark, DataLake, Snowflake, Airbyte frameworks.

Who you are

• Bachelor's or master's degree in computer science, Engineering, Data Science, Artificial Intelligence, Machine Learning, or a related technical field, or equivalent practical experience.
• 4-5 years of relevant professional experience in data engineering, AI/ML engineering, software engineering, or related technical roles, with hands-on experience building data-intensive or AI-enabled applications.
• Strong programming skills in Python, with experience developing production-quality data or AI applications.
• Experience designing and developing ETL/ELT pipelines for structured and unstructured datasets.
• Good understanding of data structures, data modelling, database schema design, data quality, and scalable data processing.
• Hands-on experience with SQL and relational databases such as PostgreSQL, MySQL, SQL Server, or equivalent.
• Experience working with data processing and analytics technologies such as Pandas, PySpark, Spark, Databricks, or equivalent frameworks.
• Experience with at least one major cloud platform - AWS, Azure, or GCP - and its data/AI services.
• Understanding of Generative AI and Large Language Model (LLM) concepts, including prompting, embeddings, tokenization, context management, and model APIs.
• Experience developing or integrating RAG-based applications, including document ingestion, chunking, embeddings, retrieval, and response generation.
• Familiarity with vector databases/vector search technologies such as Pinecone, Weaviate, Chroma, pgvector, Azure AI Search, Elasticsearch/OpenSearch, or equivalent.
• Understanding of techniques for improving retrieval and LLM application quality, including metadata filtering, hybrid search, reranking, prompt engineering, and structured outputs.
• Familiarity with AI/LLM application frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent.
• Strong interpersonal and communication skills, including the ability to explain technical concepts, data architectures, and AI approaches to colleagues and stakeholders from different disciplines.
• Curiosity, proactivity, critical thinking, and a strong willingness to learn emerging data and AI technologies.
• Ability to collaborate effectively with cross-functional and multi-office/region teams.
• Strong problem-solving mindset and ability to work through ambiguous technical and business requirements.

What makes us a great place to work

We are proud to be consistently recognized as one of the world's best places to work, a champion of diversity, and a model of social responsibility. We are a Glassdoor Best Place to Work, and we have maintained a spot in the top four since its founding in 2009. We believe that diversity, inclusion, and collaboration are key to building extraordinary teams. We hire people with exceptional talents, abilities, and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally.