Backend Developer Job at NTT DATA (Bangalore)

Backend Developer

NTT DATA

Location:
India , Bangalore

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

The Backend Developer role involves designing and maintaining scalable backend systems and APIs for AI-driven applications. Candidates should have over 5 years of experience in backend development, particularly with Python and FastAPI. Collaboration with AI/ML engineers and data scientists is essential, along with a strong understanding of scalable architectures and database management. As a Backend Developer (FastAPI), you will design, build, deploy, and maintain scalable backend systems and APIs that power AI-driven applications and data-intensive platforms. You will develop high-performance services using FastAPI and Python to support AI/ML models, LLM-powered features, and real-time data workflows in production environments. You will work closely with AI/ML engineers, data scientists, frontend developers, and DevOps teams to implement robust backend architectures that integrate AI models, vector databases, third-party APIs, and enterprise systems. This is a hands-on engineering role where you will build RESTful APIs, manage asynchronous workflows, implement authentication and authorization mechanisms, and optimize system performance. You will ensure backend reliability, scalability, and security across development and production environments. Additionally, you will monitor API performance, optimize database queries, improve model-serving latency, and enhance system architecture through continuous improvements and operational best practices.

Job Responsibility:

Design and implement scalable backend APIs using FastAPI
Integrate AI/ML models and LLM services into backend workflows
Build data processing pipelines and asynchronous background tasks
Design and optimize database schemas and queries
Implement secure authentication and authorization mechanisms
Develop and maintain API documentation (OpenAPI/Swagger)
Write clean, maintainable, and well-tested code
Perform performance tuning and latency optimization for AI model serving
Collaborate with frontend and AI teams to implement end-to-end features
Deploy services using Docker and cloud platforms
Monitor backend services and troubleshoot production issues
Maintain version control, documentation, and deployment automation
Translate business requirements into scalable technical solutions

Requirements:

5+ years of hands-on backend development experience using Python
Strong experience building production-grade APIs using FastAPI (and similar frameworks such as Flask/Django)
Proven experience working on AI/ML or LLM-based application backends
Experience integrating AI models, ML services, or inference endpoints into production systems
Strong understanding of scalable backend architecture and distributed systems
Experience working in engineering-focused roles (not purely research-based)
Degree in Computer Science, Engineering, Data Science, or related field — or equivalent practical experience
Strong hands-on experience with Python and FastAPI for building RESTful and asynchronous APIs
Experience designing and consuming APIs (REST, Webhooks, third-party integrations)
Strong understanding of async programming, concurrency, and background task processing
Experience integrating AI/ML models, LLM APIs (OpenAI, Claude, Llama, etc.), or custom model endpoints
Practical knowledge of RAG architectures and vector databases (Pinecone, Weaviate, FAISS, etc.) is a plus
Experience working with relational databases (PostgreSQL/MySQL) and ORMs (SQLAlchemy, etc.)
Knowledge of NoSQL databases (MongoDB, Redis) is an advantage
Experience implementing authentication and authorization (JWT, OAuth2, RBAC)
Experience with Docker and containerized deployments
Familiarity with Kubernetes and cloud platforms (AWS/Azure/GCP)
Experience with CI/CD pipelines and automated deployments
Strong debugging and performance optimization skills
Experience writing unit and integration tests (Pytest preferred)
Familiarity with logging, monitoring, and observability tools
Understanding of API security, rate limiting, and data protection best practices
Strong knowledge of Git and collaborative development workflows

Nice to have:

Practical knowledge of RAG architectures and vector databases (Pinecone, Weaviate, FAISS, etc.)
Knowledge of NoSQL databases (MongoDB, Redis)

Additional Information:

Job Posted:
March 25, 2026

Employment Type:

Fulltime

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