Backend Engineer (AI / LLM / Claude Applications)

Job Title: Backend Engineer (AI / LLM / Claude Applications)

Role Overview

We are looking for a skilled Backend Engineer to design, build, and scale backend systems for AI-powered applications, with a strong focus on Claude (Anthropic) / LLM-based solutions. You will work closely with AI/ML engineers, frontend developers, and product teams to integrate large language models into production-grade systems.

Key Responsibilities

• Design and develop scalable backend systems and APIs for AI-driven applications
• Integrate Claude API (Anthropic) and other LLMs (OpenAI, Azure OpenAI, etc.) into products
• Build middleware, orchestration layers, and agent frameworks for AI workflows
• Implement prompt pipelines, context management, and memory systems
• Develop high-performance REST/GraphQL APIs for AI services
• Handle real-time and asynchronous processing of AI inference workflows
• Optimize latency, cost, and throughput for LLM usage
• Implement RAG (Retrieval Augmented Generation) pipelines using vector databases
• Ensure security, compliance, and data privacy standards for AI systems
• Monitor and maintain production systems, logging, and observability
• Collaborate with DevOps for CI/CD, containerization, and cloud deployment

Required Skills & Qualifications

Core Backend Skills

• Strong experience in Python / Node.js / Java / Go
• Expertise in building scalable microservices architecture
• Solid understanding of REST APIs, GraphQL, and distributed systems
• Experience with databases: SQL PostgreSQL, MySQL), NoSQL (MongoDB, Redis, DynamoDB)

AI / LLM Experience - Claude API (Anthropic) preferred, OpenAI / Azure OpenAI / other LLMs

• Understanding of Prompt engineering, Token management & Context window optimization
• Experience building:

Chatbots, copilots, or AI agents

Data & AI Infrastructure

• Experience with vector databases:

Pinecone, Weaviate, FAISS, Chroma

• Knowledge of RAG architectures
• Familiarity with embedding models and semantic search

Cloud & DevOps

• Experience with cloud platforms: Azure / AWS / GCP
• Knowledge of Docker, Kubernetes, CI/CD pipelines, Serverless architectures