Lead AI Engineer I - R01571042

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)