Lead AI Engineer I - R01571162

• 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)

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