Lead AI Engineer I - R01571043

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)