Backend AI engineer

Role overview

Responsibilities

• check_circle Design, develop, and maintain scalable backend services and APIs using Python.
• check_circle Build and deploy enterprise-grade AI solutions on Microsoft Azure.
• check_circle Integrate Large Language Models (LLMs) and Generative AI capabilities into production applications.
• check_circle Design and implement Retrieval-Augmented Generation (RAG) architectures.
• check_circle Develop prompt engineering strategies and optimize LLM interactions for business use cases.
• check_circle Build intelligent document processing solutions leveraging LLMs and AI services.
• check_circle Integrate capabilities such as semantic search, document understanding, speech-to-text, and AI agents.
• check_circle Collaborate with cross-functional teams to ensure seamless integration of AI services and applications.
• check_circle Monitor performance, troubleshoot production issues, and continuously improve solution reliability and scalability.
• check_circle Contribute to technical architecture decisions and challenge existing implementations to improve code quality and maintainability.
• check_circle Stay up to date with emerging trends and innovations in Generative AI, LLMs, and AI engineering.
• check_circle Strong software engineering background with extensive experience in Python.
• check_circle Experience developing backend applications, microservices, and REST APIs.
• check_circle Proven experience working with Large Language Models (LLMs) and Generative AI solutions.
• check_circle Hands-on experience with Prompt Engineering beyond basic prompt creation.
• check_circle Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
• check_circle Knowledge of NLP concepts such as embeddings, semantic search, document understanding, and entity extraction.
• check_circle Experience deploying and managing cloud solutions on Microsoft Azure.
• check_circle Understanding of AI solution lifecycle, deployment, monitoring, and optimization.

Preferred qualifications

• LangChain, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks.
• Intelligent Document Processing (IDP).
• OCR and document extraction technologies.
• Speech-to-Text solutions.
• AI Agents and agentic workflows.
• Node.js development experience.
• Microsoft Bot Framework.
• Docker and containerized deployments.
• CI/CD and DevOps practices.