Backend AI engineer

We are looking for a Senior AI Engineer to join a growing team focused on building and deploying cutting-edge AI solutions in production environments.

This role combines software engineering, cloud development, and Generative AI, requiring a hands-on professional capable of designing, developing, deploying, and maintaining end-to-end AI-powered applications.

You will work closely with AI Engineers, Data Scientists, and Front-End Developers to build scalable and reliable solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud-native Azure services.

Key Responsibilities

Design, develop, and maintain scalable backend services and APIs using Python.

Build and deploy enterprise-grade AI solutions on Microsoft Azure.

Integrate Large Language Models (LLMs) and Generative AI capabilities into production applications.

Design and implement Retrieval-Augmented Generation (RAG) architectures.

Develop prompt engineering strategies and optimize LLM interactions for business use cases.

Build intelligent document processing solutions leveraging LLMs and AI services.

Integrate capabilities such as semantic search, document understanding, speech-to-text, and AI agents.

Collaborate with cross-functional teams to ensure seamless integration of AI services and applications.

Monitor performance, troubleshoot production issues, and continuously improve solution reliability and scalability.

Contribute to technical architecture decisions and challenge existing implementations to improve code quality and maintainability.

Stay up to date with emerging trends and innovations in Generative AI, LLMs, and AI engineering.

Required Experience & Skills Technical Skills

Strong software engineering background with extensive experience in Python.

Experience developing backend applications, microservices, and REST APIs.

Proven experience working with Large Language Models (LLMs) and Generative AI solutions.

Hands-on experience with Prompt Engineering beyond basic prompt creation.

Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

Knowledge of NLP concepts such as embeddings, semantic search, document understanding, and entity extraction.

Experience deploying and managing cloud solutions on Microsoft Azure.

Understanding of AI solution lifecycle, deployment, monitoring, and optimization.

Nice to Have

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.

Interested in learning more? We’d love to hear from you. Reach out and let’s schedule a conversation to discuss the opportunity.