Analyst - R01571043

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) Additional Information: Location: Bangalore (Hybrid work arrangement)