Associate Consultant / Consultant

LinkedIn’s interview process typically involves three rounds: a technical coding round, a system design or AI‑specific round, and a behavioral/HR round. Candidates can expect challenging questions on data structures, algorithms, and real‑world problem solving, along with discussions on teamwork, leadership, and cultural fit. Preparation should focus on coding practice, system design fundamentals, and clear communication of thought processes.

Round 1: Technical – coding & AI framework questions → Round 2: Technical – system design & RAG/agent workflow → Round 3: HR & cultural fit

LinkedIn fosters a collaborative, data‑driven environment that encourages continuous learning and innovation. Employees enjoy a healthy work‑life balance, flexible working arrangements, and ample opportunities for career growth through internal mobility and skill development programs.

Bachelor’s or Master’s degree in Engineering (B.E/B.Tech/M.E/M.Tech) in a relevant field; 1–6 years of professional experience; strong Python programming skills; proven experience building production‑grade AI solutions; knowledge of RAG, LangChain, LangGraph, and vector databases; experience with model optimization and secure on‑prem deployments; familiarity with API design, ETL, and web scraping; preferred domain knowledge in Risk, Treasury, Banking, or Financial Services.

KPMG is one of the world’s leading professional services firms, offering audit, tax, advisory, and consulting services to a broad range of industries. With a strong presence in India, KPMG’s Mumbai office serves a diverse client base spanning banking, finance, insurance, and technology sectors. The firm is known for its collaborative culture, emphasis on continuous learning, and commitment to delivering high‑quality, innovative solutions to complex business challenges. The Associate Consultant / Consultant role is a senior‑level position focused on Generative AI, Agentic AI, and enterprise‑grade AI engineering. Candidates will be responsible for designing, developing, and deploying production‑ready AI solutions that integrate with enterprise data pipelines and secure on‑premises environments. The role requires a blend of software engineering, data engineering, and AI research skills, with a strong emphasis on Python and modern AI frameworks. Key responsibilities include: 1. Building end‑to‑end RAG and GraphRAG pipelines for document intelligence, forecasting, and decision support. 2. Designing and implementing LangChain and LangGraph agent workflows that interact with external APIs and internal data sources. 3. Optimizing open‑source LLMs and OCR models for CPU‑constrained, secure deployments using quantization, compression, and memory‑optimization techniques. 4. Developing FastAPI microservices and Streamlit dashboards to expose AI capabilities to business users. 5. Creating scalable ETL pipelines, web‑scraping routines (BeautifulSoup, Selenium), and REST API integrations for data ingestion. 6. Ensuring data quality, governance, and compliance in all AI pipelines. 7. Conducting AI evaluation, monitoring, and observability to maintain model performance and reliability. 8. Collaborating with risk, treasury, and banking domain experts to tailor AI solutions to financial services. 9. Participating in research and prototyping of emerging foundation models such as TabPFN and TimesFM. 10. Mentoring junior engineers and contributing to knowledge sharing within the team. Tech stack: Python, Pandas, Polars, PyTorch, FastAPI, Streamlit, LangChain, LangGraph, RAG, GraphRAG, vector databases (FAISS, ChromaDB, Pinecone, Milvus), foundation models (TabPFN, TimesFM), Docker, Kubernetes, CI/CD, secure deployment tools. Growth path: Starting as an Associate Consultant, professionals can progress to Senior Consultant, Lead Consultant, Manager, and eventually Principal Consultant or Director, with opportunities to specialize in AI strategy, data science, or domain‑specific consulting. Why join: KPMG offers a global platform, exposure to high‑impact projects, a culture of innovation, and a strong focus on professional development. The role provides hands‑on experience with cutting‑edge AI technologies in real‑world enterprise settings, making it an ideal fit for engineers who want to shape the future of AI in business. Overall, this position is a rare blend of advanced AI engineering, data science, and consulting, offering a challenging yet rewarding career path for experienced professionals.