Babaji .s

Having 3.6 years of professional experience as an AI Engineer, specializing in designing, developing, integrating, and deploying AI/ML and Generative AI solutions across diverse business domains. Strong proficiency in Python, Machine Learning, Deep Learning, Generative AI, NLP, and Computer Vision, with hands-on experience developing scalable and production-ready AI applications. Experienced in developing LLM-powered applications using LLMs, RAG, AI Agents, LangChain, and LangGraph for intelligent automation, knowledge retrieval, and enterprise AI use cases.

Hands-on experience with PyTorch, TensorFlow, Scikit-learn, and Hugging Face for model development, training, evaluation, optimization, and implementation of AI/ML solutions. Skilled in building RAG pipelines using embeddings, Vector Databases, Elasticsearch, semantic search, document processing, and context-aware response generation. Proficient in developing scalable AI APIs and backend services using FastAPI and integrating AI solutions with PostgreSQL, MongoDB, Redis, and enterprise applications.

Experienced in Docker, Kubernetes, Git, GitHub, CI/CD, MLflow, and MLOps for containerization, model lifecycle management, automated deployment, monitoring, and production support. Hands-on experience with AWS for deploying and managing cloud-based AI/ML applications and scalable production workloads. Experienced in leveraging GitHub Copilot, Cursor AI, ChatGPT, and Claude to accelerate development, debugging, prototyping, code optimization, and productivity.

Strong analytical, problem-solving, and collaboration skills with experience working in Agile environments and delivering scalable, reliable, and business-focused AI solutions from requirement analysis through production deployment.

AI Engineer at Accenture (Payroll: ANTS IT Solutions Pvt LTD) (2023-02 – Present)

AI Engineer

Worked on an enterprise Banking Assistant Portal designed to provide intelligent customer support for account-related queries, banking products, loan information, transaction assistance, FAQs, and policy-related queries using Generative AI and LLM technologies.

• Developed AI-powered banking solutions using Python, LLMs, Generative AI, RAG, LangChain, and LangGraph for intelligent customer assistance and knowledge retrieval.
• Designed RAG pipelines for banking policies, product documentation, FAQs, and service-related documents using document processing, embeddings, vector search, and contextual response generation.
• Developed scalable REST APIs using FastAPI and integrated AI services with PostgreSQL, Vector Databases, and existing banking application services.
• Implemented AI Agent workflows using LangGraph for multi-step customer queries, information retrieval, and tool-based business workflows.
• Leveraged GitHub Copilot, Cursor AI, and Claude for code generation, debugging, refactoring, unit test creation, documentation, and accelerating AI application development.
• Containerized AI applications using Docker and supported AWS deployments through CI/CD pipelines for reliable application delivery.
• Used MLflow for experiment tracking, model evaluation, version management, and maintaining reproducible AI/ML workflows.
• Collaborated with developers, data engineers, DevOps engineers, business analysts, and product owners in Agile Scrum to troubleshoot issues, optimize application performance, and deliver production-ready AI solutions.

AI Engineer

Worked on an enterprise Healthcare Analytics Portal designed to help healthcare organizations analyze operational and clinical data, retrieve healthcare information, generate insights, and support data-driven decision-making using Machine Learning, NLP, and Generative AI technologies.

• Developed Machine Learning and NLP solutions using Python, PyTorch, Scikit-learn, Hugging Face, and LLMs for healthcare data analysis, classification, information extraction, and intelligent insights.
• Built RAG-based healthcare knowledge retrieval solutions using Elasticsearch and Vector Databases to retrieve relevant information from approved healthcare documentation and knowledge sources.
• Developed scalable FastAPI services for integrating ML models, LLM applications, analytics workflows, and healthcare backend systems.
• Implemented data preprocessing, feature engineering, model training, evaluation, and optimization workflows for healthcare analytics and NLP use cases.
• Integrated PostgreSQL and Redis for managing application, analytics, and workflow data while supporting efficient data access and caching.
• Containerized AI services using Docker and deployed scalable workloads using Kubernetes and AWS to support reliable production inference and application availability.
• Implemented MLOps practices using MLflow, Git, GitHub, and CI/CD pipelines for experiment tracking, model versioning, deployment automation, and production model lifecycle management.
• Collaborated with data engineers, software developers, DevOps teams, healthcare stakeholders, and product owners in Agile Scrum to analyze requirements, troubleshoot issues, improve model performance, and deliver scalable AI solutions.
• Collaborated with business analysts, developers, QA teams, and DevOps engineers in Agile Scrum environments to enhance automation coverage, reduce manual testing effort, and ensure high-quality software releases.

B.Tech – Sree Vidyanikethan Engineering College (2020 – 2023)