About the role
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)