₹11L – ₹24L a year estimatetypical for IT Jobs in India, 907 posts
Posted 1 month ago Last checked 2 hr ago
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Role at a glance
You will
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
Experience
2–4 years
Education
Bachelor's degree
Must-have skills
AWSAngularCI/CDDatabricksDjangoDocker
Work mode
Hybrid
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Job description
Location: Gurgaon, Haryana, India Department: CTO Office
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)
This page is for Indian job seekers preparing for cloud engineer, DevOps, backend and solutions architect roles that list AWS as a skill, whether you are a fresher with a first certification or an experienced engineer moving into a senior role. It covers 60 questions in three levels: core services and concepts, then design and configuration choices for one to three years of experience, and finally scenario, security, cost and troubleshooting questions asked in senior rounds. Read each answer, explain it aloud in your own words, and try the CLI commands in a practice account with a billing alert set.
Questions you may be asked
What is the difference between an AWS Region and an Availability Zone?
Explain the AWS shared responsibility model.
What is Amazon EC2, and how do you read an instance type name like m7g.large?
What is Amazon S3, and what are its main storage classes?
