Back End Developer

Title: Backend Developer

Location: Jaipur, Noida, Gurgaon, Pune, Bengaluru, Hyderabad

Duration: Fulltime

Experience: 35 years

Role Overview

We are looking for a skilled Backend Developer to build, scale, and optimize high-performance backend systems supporting AI-driven applications, data platforms, and agentic workflows. The role involves designing APIs, integrating LLM-based systems, handling large-scale data pipelines, and ensuring secure, reliable, and scalable backend services.

Key Responsibilities

Design, develop, and maintain scalable backend services using Python, with strong handling of synchronous and asynchronous execution models.

Build and deploy backend systems that support LLM-based applications, including prompt-driven workflows, RAG pipelines, and fine-tuned models.

Develop API-first architectures using FastAPI, including middleware design, authentication mechanisms, ORM-based database interactions, migrations using Alembic, and proxy/networking configurations.

Work with agentic frameworks such as LangChain and LangGraph to orchestrate complex AI workflows, and use LangSmith / LangFuse for observability, tracing, and evaluation.

Build and maintain data pipelines leveraging Databricks, including Delta Lake and core Databricks services for reliable data storage and processing.

Integrate message queue and streaming systems such as Redis for event-driven and asynchronous communication.

Develop backend services that interact with cloud infrastructure, primarily using AWS core services for compute, storage, networking, and deployment.

Collaborate closely with data scientists, ML engineers, and platform teams to productionize AI solutions with strong focus on performance, security, and scalability.

Required Skills & Qualifications

Strong backend development experience in Python, including async frameworks and concurrency handling.

Hands-on experience with FastAPI and modern backend architecture patterns.

Solid understanding of LLMs, prompt engineering, RAG, and fine-tuning workflows.

Experience with agent-based systems and LLM orchestration frameworks.

Working knowledge of Databricks and Delta Lake for data engineering use cases.

Experience with event-driven architectures using Kafka or NATS.

Familiarity with AWS services and cloud-native backend deployments.

Understanding of containerization and orchestration concepts (basic level acceptable).

Good to Have

Exposure to LLMOps / Model observability practices.

Experience deploying AI-backed APIs in production environments.

Understanding of backend security, authentication flows, and network-level considerations.