AI Engineer (Python) Analyst

Analyst - AI Engineer (Python)

Our team of dedicated Python AI Engineer recognizes the powerful impact that software engineering can have on creating value for organizations. We adopt a comprehensive approach, leveraging our technical expertise to solve complex challenges with solutions that allow our clients to excel.

At KPMG, we are harnessing the power of Generative AI (GenAI) to reimagine and transform various aspects of our business operations and client services. As part of the AI & Digital Innovation organization, the AI & Data Labs team is expanding to meet growing business demand.

The Analyst, GenAI will play a pivotal role in designing and delivering enterprise-grade GenAI solutions, with a strong focus on scalability, compliance, and business value. Based in India, this role will support global initiatives and work closely with senior leaders across India and US.

Key Responsibilities:

• Design and develop end-to-end AI applications (frontend, backend, and AI/ML layers)
• Build, train, and deploy machine learning / GenAI models (e.g., LLMs, RAG pipelines)
• Develop APIs and microservices for model serving and integration
• Build responsive user interfaces for AI-driven applications
• Integrate AI solutions with enterprise systems and data platforms
• Ensure scalability, performance, and reliability of AI applications
• Implement MLOps practices (CI/CD, monitoring, model versioning)

• Collaborate with data engineers, product teams, and business stakeholders

   

   

Required Skills & Qualifications:

• Bachelor’s/Master’s degree in Computer Science, AI, or related field
• Strong programming skills in Python and one frontend/backend framework (e.g., React, Node.js, FastAPI)
• Experience with machine learning / deep learning frameworks (Scikit-learn, TensorFlow, PyTorch)
• Hands-on experience building REST APIs and web applications
• Familiarity with databases (SQL/NoSQL) and data pipelines
• Experience with cloud platforms (Azure, AWS, or GCP)

• Strong understanding of software engineering best practices

   

 

Nice to Have (Highly Valuable):

• Experience with GenAI/LLMs (OpenAI, Azure OpenAI, LangChain, RAG architectures)
• Knowledge of vector databases (FAISS, Pinecone, Weaviate)
• Exposure to Docker, Kubernetes, and DevOps/MLOps pipelines
• Experience in building AI-powered enterprise applications or agents

BE/ B.Tech or equivalent

Experience Level

Mid Level