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. TechB. 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.