Analyst - R01571044

Brillio; Bengaluru; Hybrid; INR 900,000 - 1,500,000; Full time

Job summary

Brillio is seeking an Analyst to design and deploy end-to-end full-stack data science applications with cloud-native architectures and agentic AI frameworks. The role requires 2–4 years of hands-on experience in building scalable frontend, backend, and API components.

You will work with Azure/AWS/GCP, Docker and Kubernetes, and contribute to AI-powered workflows using LangChain, LlamaIndex, and related tools. A Bachelor’s degree in CS/AI/DS is expected, with a hybrid Bengaluru work arrangement.

Qualifications

• Experience in full-stack development covering frontend, backend and APIs.
• Cloud-native architectures and agentic AI frameworks exposure.
• Hands-on with Azure/AWS/GCP cloud platforms and containerized deployments.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Familiarity with LangChain, LlamaIndex, and related AI tooling.

Responsibilities

• Design and develop end-to-end full-stack applications across UI, API, and services.
• Build agentic AI apps using multi-agent systems and autonomous workflows.
• Develop scalable backend systems with microservices and event-driven patterns.
• Implement cloud-native deployments on Azure, AWS, and GCP.
• Integrate LLM-based frameworks and agent orchestration tools into workflows.
• Uphold code quality, testing, observability, security and performance.
• Collaborate with cross-functional teams to align solutions with business needs.
• Contribute to design reviews and architectural decisions for AI-driven systems.

Skills

Full-stack development

Frontend frameworks

Backend development

RESTful API design

Cloud platforms (Azure/AWS/GCP)

Docker & Kubernetes

CI/CD

Agentic AI frameworks

Prompt engineering

RAG techniques

Education

Bachelor's degree in CS/AI/DS

Tools

LangChain

LlamaIndex

Semantic Kernel

AutoGen

CrewAI

Job description

Analyst

Job Requirements

Experience Range: With at least 2 to 4 years of experience in full-stack data science, including practical exposure to cloud-native architectures and agentic AI frameworks

Key Responsibilities

• Design and develop end-to-end full-stack applications, covering frontend, backend, and API components
• Build and deploy agentic AI applications using multi-agent systems and autonomous workflows
• Implement scalable backend systems with microservices and event-driven architectures to support intelligent solutions
• Develop cloud-native solutions on platforms such as Azure, AWS, and GCP, ensuring robust and scalable deployments
• Integrate LLM-based frameworks and agent orchestration tools to enable adaptive and intelligent workflows
• Enforce best practices in code quality, testing, debugging, observability, performance optimization, security, and scalability
• Collaborate with cross-functional teams to deliver technical solutions aligned with business requirements
• Contribute to design reviews and architectural decisions for AI-driven systems

Required Skills

• Full-stack development with React, Angular, or Vue for frontend
• Backend development using Node.js, Java Spring Boot, or Python frameworks (FastAPI, Django)
• RESTful API design and microservices architecture
• Experience with Azure, AWS, and GCP cloud platforms
• Hands-on experience with Docker containers and Kubernetes
• CI/CD pipeline implementation
• Agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI
• Prompt engineering and Retrieval-Augmented Generation (RAG) techniques

Preferred Skills

• Familiarity with vector databases such as FAISS or Pinecone
• Knowledge of event streaming systems like Kafka or Pub/Sub
• Experience with federated learning or privacy-preserving algorithms
• Contributions to open-source projects or hackathons in AI/ML or full-stack domains
• Experience with model experimentation platforms such as Domino Datalabs or Databricks ML

Desired Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related discipline
• Certification in cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer)
• Certification in full-stack development or AI frameworks (e.g., Full Stack Web Development, TensorFlow Developer Certificate)

Location: Bangalore (Hybrid work arrangement)