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)
