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)