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 componentsBuild and deploy agentic AI applications using multi-agent systems and autonomous workflowsImplement scalable backend systems with microservices and event-driven architectures to support intelligent solutionsDevelop cloud-native solutions on platforms such as Azure, AWS, and GCP, ensuring robust and scalable deploymentsIntegrate LLM-based frameworks and agent orchestration tools to enable adaptive and intelligent workflowsEnforce best practices in code quality, testing, debugging, observability, performance optimization, security, and scalabilityCollaborate with cross-functional teams to deliver technical solutions aligned with business requirementsContribute to design reviews and architectural decisions for AI-driven systemsRequired Skills:
Full-stack development with React, Angular, or Vue for frontendBackend development using Node.js, Java Spring Boot, or Python frameworks (FastAPI, Django)RESTful API design and microservices architectureExperience with Azure, AWS, and GCP cloud platformsHands-on experience with Docker containers and KubernetesCI/CD pipeline implementationAgentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAIPrompt engineering and Retrieval-Augmented Generation (RAG) techniquesPreferred Skills:
Familiarity with vector databases such as FAISS or PineconeKnowledge of event streaming systems like Kafka or Pub/SubExperience with federated learning or privacy-preserving algorithmsContributions to open-source projects or hackathons in AI/ML or full-stack domainsExperience with model experimentation platforms such as Domino Datalabs or Databricks MLDesired Qualifications:
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related disciplineCertification 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)
