Jatin Raheja
Result driven professional targeting roles in AI Engineering, Generative AI, MLOps, and Python Back-end Development across organizations preferably in Delhi NCR, Bengaluru, and Hyd
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About
Impact-oriented AI Engineer with over 5 years of experience in delivering enterprise-grade solutions using Generative AI, distributed systems, and cloud-native architectures. Drove end-to-end implementation of LLM-powered applications, enabling intelligent automation of complex business workflow in healthcare and enterprise ecosystems. Displayed strong capability in building scalable microservices and backend systems, ensuring high availability, modularity, and performance optimization.
Leveraged cloud infrastructure and container orchestration to streamline deployments and enhance system reliability in production environments. Improved operational efficiency by optimizing pipelines, reducing latency, and enhancing output accuracy. Brought a strong blend of analytical thinking, system design expertise, and execution excellence to solve large-scale engineering challenges.
Consistently delivered robust, maintainable, and scalable solutions, aligned with evolving industry standards and hiring expectations.
Experience
AI Engineer / Sr. Software Engineer at Carelon Global Solutions (2023-02 – Present)
- Developing RAG-based intelligent systems using LLM, OpenAI, Langchain, Langgraph, VectorDB (FAISS, ChromaDB) to automate summarization of medical documents for prior authorization workflow.
- Enhancing response quality by optimizing prompt engineering and post-processing techniques, aligning outputs with clinician feedback.
- Building production-grade pipelines integrating Generative AI, AWS Textract (OCR), and cloud services (AWS S3, EC2, Lambda) to ensure scalable execution.
- Architecting microservices-based systems using FastAPI, Flask, Sanic, Django REST Framework, enabling modular service orchestration.
- Integrating services through event-driven architecture using RabbitMQ and Kafka, implementing publisher-consumer mechanisms for real-time communication.
- Managing containerized deployments using Docker, Kubernetes (kubectl) with monitoring and scaling through HPA and configmaps.
- Implementing CI/CD pipelines using ArgoCD and GitHub Actions, improving deployment efficiency and reducing release cycles.
- Automating back-end workflow by developing Python-based cron jobs, improving reporting and notification efficiency.
- Monitored pods and tracked logs in production environment using ArgoCD and AWS cloudwatch.
Software Engineer at FelixHealthcare.AI (2020-12 – 2023-01)
- Developed back-end systems using Python and FastAPI, enabling scalable REST API development for enterprise applications.
- Built recruitment platform Kiniso, implementing APIs for entities such as Companies, Jobs, Talent, and Assignments using MongoDB.
- Applied MVC architecture principles, improving modularity, maintainability, and extensibility of back-end systems.
- Deployed applications on Google Cloud Platform using Docker containers, ensuring high availability and scalability.
- Designed machine-learning models using Pandas, NumPy, NLP techniques, improving buyback decision efficiency by 50%.
- Processed and categorized large datasets using Natural Language Processing, enhancing model accuracy and business insights.
- Collaborated in Agile sprint cycles using Jira and Bitbucket, ensuring continuous delivery and iterative improvements.
Education
B.E in CSE – Chitkara University
Class XII in CBSE – Himland Public School
Class X in CBSE – Jesus Saviour's School



