Lead AI Engineer I - R01571162

Lead AI Engineer I

Job requirements
Experience Range: With at least 4 to 6 years of experience in ML engineering, including hands-on work with cloud-native architectures, agentic AI frameworks, and scalable full-stack systems Key Responsibilities: Design and build end-to-end full-stack intelligent applications, integrating frontend, backend, and APIs using modern frameworks Develop and deploy cloud-native solutions leveraging platforms such as Azure, AWS, and GCP Build and implement agentic AI applications, including multi-agent systems and autonomous workflows Develop scalable backend systems using microservices and event-driven architectures, optimizing for performance, security, and scalability Work with LLM-based frameworks and agent orchestration tools to create intelligent, adaptive workflows Ensure best practices in code quality, testing, debugging, observability, and performance optimization Collaborate with cross-functional teams to translate business requirements into robust technical solutions and participate in architectural decisions Required Skills: Advanced proficiency in Python and JavaScript/TypeScript Experience with frontend frameworks such as React, Angular, or Vue Backend expertise with Node.js, Java Spring Boot, or Python (FastAPI, Django) Hands-on experience with cloud platforms (Azure, AWS, GCP) Proficiency in containers (Docker) and basic understanding of Kubernetes RESTful API and microservices design Experience with agentic AI frameworks such as LangChain, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI Understanding of prompt engineering and Retrieval-Augmented Generation (RAG) Familiarity with CI/CD pipelines Preferred Skills: Experience with autonomous systems or multi-agent architectures Knowledge of conversational AI or AI-driven automation workflows Familiarity with vector databases (FAISS, Pinecone, etc.) Expertise in event streaming systems like Kafka or Pub/Sub Contributions to open-source projects or hackathons in AI/ML or full stack domains Desired Qualifications: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related discipline Certification in cloud platforms (e.g., AWS Certified Machine Learning Specialty, Azure AI Engineer Associate, Google Professional Machine Learning Engineer) Relevant certification in agentic AI frameworks or full-stack development (e.g., TensorFlow Developer Certificate, React Professional Certification) Additional Information: Location: Bangalore (Hybrid)