About the Role
We are seeking a Senior FullStack Developer with deep expertise in both deepbackend (Priority) and well-understanding frontend technologies to build and maintain the scalable systems that power our AI and LLMbased products. While the role expands to fullstack responsibilities, the core focus remains on designing robust backend services, integrating machinelearning models, and managing the infrastructure that supports large language models.
Key Responsibilities
- Design & implement backend services and APIs using Golang and Python (including microservices architecture)
- Collaborate with ML engineers to deploy, monitor, and integrate machinelearning models into production pipelines
- Develop and maintain infrastructure for LLMs and AI agents, ensuring high performance, scalability, and reliability
- Manage and optimize databases (MySQL, MongoDB) and work with vector databases or RAG systems where needed
- Utilize AIassisted coding tools such as Codex and Claude Code to accelerate development
- Build modern, responsive UI components using React and MUI 5, delivering seamless user experiences.
- Implement serverside logic with Java, Spring, and Spring Boot, enabling robust, enterprisegrade services.
- Deploy and orchestrate applications on Kubernetes clusters, leveraging AWS and Azure infrastructure services.
Required Qualifications
- 5+ years of professional experience in backend development (Golang/Python) and fullstack development (React, Java/Spring).
- Strong understanding of AI Agentic workflows and experience integrating ML models into production
- Proven experience with MySQL, MongoDB, and optionally vector databases or RAG systems
- Handson experience with microservices, cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes)
- Familiarity with LLM and AIagent frameworks, and the ability to build supporting infrastructure
Bonus Skills
- Experience with MUI 5 for building modern UI components.
- Proficiency in React (hooks, context, performance optimization).
- Strong Java development background, especially with Spring and Spring Boot.
- Knowledge of Kubernetes advanced concepts (Helm, operators, CI/CD pipelines).
- Handson experience managing AWS services (ECS/EKS, Lambda, S3, RDS) and Azure services (AKS, Functions, Cosmos DB).
- Exposure to MLOps tools such as MLflow, Kubeflow, SageMaker.
- Experience with vector databases, retrievalaugmented generation (RAG) systems, or embeddings.
