Senior Backend Engineer

We are looking for a highly skilled Senior Backend Engineer to design, develop, and scale AI-powered applications and backend platforms. The ideal candidate will have strong expertise in backend engineering, cloud-native architectures, Retrieval-Augmented Generation (RAG) systems, Agentic AI frameworks, and production-grade LLM deployment. This role requires hands-on experience in building scalable AI solutions, optimizing cloud infrastructure, and ensuring reliability, observability, and security in production environments.

The Candidate Will Have Responsibilities Across The Following Functions Backend Engineering and Platform Development:

• Design, develop, and maintain scalable backend services using Python, FastAPI, and asynchronous microservices architectures.
• Build and optimize data-intensive applications using PostgreSQL, Redis, MongoDB, or equivalent technologies at production scale.
• Develop high-performance APIs and distributed systems to support AI-driven applications.

Cloud Infrastructure And DevOps

• Architect and manage cloud-native applications on AWS or GCP.
• Deploy and operate services using ECS, Lambda, Cloud Run, and other cloud-native technologies.
• Implement and manage Infrastructure as Code (IaC) using Terraform or equivalent frameworks like Pulumi, CloudFormation.
• Build and optimize CI/CD pipelines for reliable and automated deployments.

Retrieval-Augmented Generation (RAG) And Agentic AI Systems

• Design and implement production-grade RAG pipelines.
• Build hybrid retrieval systems using BM25 pgvector, vector databases, and semantic search techniques.
• Optimize retrieval accuracy, latency, and scalability for enterprise use cases.
• Build agentic workflows (LangGraph or similar) with tool calling, multi-step orchestration, and production guardrails like fallback routing and human-in-the-loop controls.

Monitoring And Observability

• Instrument backend services end-to-end with metrics, distributed tracing, and structured logging using OpenTelemetry.
• Hands-on with some observability stacks: Prometheus + Grafana, Datadog/New Relic, and centralized logging (ELK/Loki).
• Build actionable dashboards and alerts to detect latency, errors, and resource bottlenecks before customer impact.
• Experience with LLM/AI system observability token usage, latency, and quality tracing (Langfuse, LangSmith, Arize).

Requirements

• 4+ years of experience in backend development.
• B. E. \B. Tech\B. S. Candidates' entries with significant prior experience in the fields above will be considered.
• Strong experience in Python development and FastAPI.
• Hands-on experience with asynchronous microservices architectures.
• Expertise in PostgreSQL, Mongodb, Redis, and distributed backend systems.
• Experience with AWS or GCP cloud platforms and Infrastructure as Code (Terraform, Cloudformation, or equivalent).
• Strong understanding of CI/CD pipelines and DevOps best practices.
• Proven experience building and deploying RAG systems in production environments.
• Experience with LangGraph, tool calling, and agent-based AI architectures.
• Experience with development using AI coding agents like Claude Code, Cursor, or equivalent.
• Guardrails in production: model fallback routing, prompt-injection defense, and token cost budgets.
• Demonstrated ownership mindset with the ability to drive projects and deliver high-quality solutions.
• Experience in mentoring team members, conducting code reviews, and sharing best practices. This job was posted by Archana Agrawal from InFoCusp Innovations.