1. Data Scientist – Artificial Intelligence (Agentic AI & Process Intelligence)

Experience: 6–9 Years

Location: Bangalore

Job Summary

We are seeking an experienced Data Scientist – Artificial Intelligence with expertise in Agentic AI, Process Intelligence, and Intelligent Automation to design and implement AI-driven solutions that optimize enterprise supply chain operations. The ideal candidate should have hands-on experience in Generative AI, Process Mining, RAG architectures, workflow automation, and LLM-based applications. This role focuses on building intelligent systems capable of analyzing, recommending, and automating business processes across planning, manufacturing, and logistics.

Key Responsibilities

• Design, develop, and deploy Agentic AI solutions for enterprise business processes.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using enterprise knowledge sources.
• Develop AI copilots and conversational assistants powered by Large Language Models (LLMs).
• Perform process discovery, conformance analysis, and root-cause analysis to identify operational inefficiencies.
• Develop Process Intelligence dashboards and analytical solutions using operational KPIs and business data.
• Build workflow automation using platforms such as n8n, Apache Airflow, or Make.
• Design intelligent automation solutions that combine AI recommendations with automated workflows.
• Develop Proof of Concepts (POCs) and Minimum Viable Products (MVPs) for emerging AI technologies.
• Collaborate with business stakeholders to deliver scalable AI-driven digital transformation initiatives.
• Establish reusable AI frameworks, best practices, and automation standards.

Required Skills

• 6–9 years of experience in Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or Intelligent Automation.
• Strong programming skills in Python and API development.
• Hands-on experience with LangChain, LangGraph, CrewAI, Semantic Kernel, or similar Agentic AI frameworks.
• Strong experience building RAG-based AI applications.
• Experience with vector databases such as Pinecone, FAISS, ChromaDB, or Qdrant.
• Good understanding of LLMs, Prompt Engineering, Embeddings, Function Calling, and AI evaluation techniques.
• Experience with workflow orchestration tools such as n8n, Apache Airflow, or Make.
• Strong SQL and Data Engineering fundamentals.
• Knowledge of Process Mining concepts including Process Discovery, Conformance Checking, and Performance Analysis.
• Experience with cloud AI platforms such as Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Familiarity with Docker, Git, and CI/CD practices.
• Strong analytical, communication, and stakeholder management skills.

Preferred Skills

• Experience with Celonis, SAP Signavio, or other Process Mining platforms.
• Knowledge of Supply Chain, Manufacturing, Logistics, or ERP systems (SAP preferred).
• Exposure to Digital Twins, Decision Intelligence, and Autonomous Planning.
• Understanding of Lean, Six Sigma, and Continuous Improvement methodologies.
• Experience working in global, cross-functional teams.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Systems, or a related discipline.
• Certifications in Generative AI, Machine Learning, Data Engineering, Agile, or Lean Six Sigma are preferred.

2. Data Scientist – Artificial Intelligence (Generative AI / LLM Engineer)

Experience: 3–6 Years

Location: Bangalore

Job Summary

We are looking for a Data Scientist – Artificial Intelligence with strong expertise in Generative AI and Large Language Models (LLMs). The ideal candidate should have hands-on experience in developing AI-powered applications using Retrieval-Augmented Generation (RAG), Prompt Engineering, Embeddings, and modern LLM frameworks. The candidate will contribute to designing, developing, and optimizing scalable AI solutions for enterprise use cases.

Key Responsibilities

• Design, build, and deploy AI applications powered by Large Language Models.
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines.
• Create effective prompts to improve LLM performance across business use cases.
• Implement embedding models and vector search solutions for semantic retrieval.
• Fine-tune, evaluate, and optimize LLM-based applications.
• Integrate AI models with enterprise applications through APIs.
• Collaborate with data engineers and software development teams to deploy production-ready AI solutions.
• Monitor model performance and improve AI application accuracy and efficiency.
• Participate in AI experimentation, prototyping, and solution development.

Required Skills

• 3–6 years of experience in Artificial Intelligence, Machine Learning, Data Science, or Software Development.
• Strong proficiency in Python.
• Hands-on experience with Large Language Models (LLMs).
• Strong understanding of Retrieval-Augmented Generation (RAG).
• Experience with Embeddings and vector databases.
• Expertise in Prompt Engineering.
• Hands-on experience developing and deploying LLM-based applications.
• Experience using AI-enabled development environments such as GitHub Copilot or similar AI coding assistants.
• Good understanding of REST APIs and AI model integration.

Preferred Skills

• Knowledge of LLM Logging and Monitoring.
• Understanding of Data Privacy, Security, and Access Control for AI applications.
• Knowledge of LLM Cost Optimization techniques.
• Experience with LLMOps pipelines, model deployment, and lifecycle management.
• Exposure to Azure OpenAI, AWS Bedrock, Vertex AI, or similar cloud AI platforms.

Educational Qualification

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
• Certifications in Generative AI, Machine Learning, or Cloud AI technologies are an added advantage.