Backend AI engineer
About the Role
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.
- 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.