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Analyst - R01571043

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Hybrid

Analyst - R01571043

Brillio

Analyst - R01571043

Skills

Google Cloud PlatformDockerReactNodeDjangoPythonData ScienceJavaMicroservicesTensorFlowSpring BootKafkaDatabricksMachine LearningAIAWSKubernetesFastAPIFullstack DevelopmentAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

12 September 2026

What they need


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)

Additional Information: Location: Bangalore (Hybrid work arrangement)

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