Afsara Kainat
DevOps Engineer | MLOps & LLMOps Enthusiast | AWS Certified | Automating AI-Driven Cloud Solutions
- Role
- Senior Analyst at Capgemini
- Location
- Mumbai, MH, IN
- LinkedIn followers
- 500 followers
About Afsara Kainat
AWS Certified Cloud & DevOps Engineer with 2 years of hands-on experience in building and operating cloud-native backend and AI-enabled systems. My core expertise lies in AWS infrastructure automation, CI/CD pipelines, containerized deployments, and backend engineering, with growing exposure to AI and MLOps workflows.At Capgemini, I have worked on automating secure and scalable AWS environments using Infrastructure as Code (CloudFormation, Terraform), designing CI/CD pipelines with GitHub Actions, and deploying Dockerized services on Kubernetes (EKS). I have also contributed to monitoring and observability using CloudWatch, Prometheus, and Grafana to support reliable production systems.Alongside DevOps and backend responsibilities, I have hands-on experience integrating AI and LLM-based capabilities into backend services using Python, LangChain, AutoGen, Hugging Face models, and OpenAI APIs for prompt-driven automation and intelligent workflows. I have supported model deployment, versioning, and experimentation using tools like MLflow and FastAPI, gaining practical exposure to MLOps and LLMOps concepts.With a strong foundation in Python, Java, and Node.js, and experience across Spring Boot, Express.js, and relational/non-relational databases, I enjoy working at the intersection of cloud engineering, automation, and AI systems. I am actively upskilling in advanced MLOps practices and aim to grow into DevOps / MLOps / AI platform engineering roles.
Experience
Senior Analyst
Jul 2025 — Present
Automated AWS cloud infrastructure using CloudFormation, IAM, Lambda, and STS for secure and scalable environments.Designed and maintained CI/CD pipelines using GitHub Actions to support multi-environment deployments.Containerized backend and AI services using Docker and deployed workloads on Amazon EKS.Supported AI model deployment workflows using MLflow and FastAPI, gaining hands-on exposure to MLOps practices.Integrated LLM-powered backend APIs using LangChain and prompt engineering for automation use cases.Implemented monitoring and observability using CloudWatch and Grafana/Prometheus to improve system reliability.
Education
JIS College of Engineering
Bachelor of Technology - BTech, Computer Science Engineering
2019 — 2023
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