Senior Backend AI Engineer

We are seeking an AI Engineer to design, build, and deploy AI-powered capabilities within our product.

This role focuses on integrating machine learning models and large language models (LLMs) into scalable software systems and delivering reliable AI-driven features to production.

The AI Engineer works at the intersection of software engineering, AI systems, and infrastructure.

transforming AI technologies into practical applications.

Responsibilities:

• Build applications powered by machine learning and large language models (LLMs).

• Implement capabilities such as intelligent assistants, semantic search, automation, and recommendation systems.

• Integrate AI functionality into backend services and product workflows.

• Design and implement retrieval pipelines, embedding pipelines, and inference workflows.

• Build Retrieval-Augmented Generation (RAG) systems and AI-driven services.

• Create scalable AI architectures capable of handling production workloads.

• Package and deploy AI models as production services.

• Optimize inference performance, scalability, and latency.

• Monitor AI services to ensure reliability and performance.

• Develop backend services and APIs that expose AI capabilities.

• Integrate AI systems with databases, internal services, and external APIs.

• Contribute to system architecture and microservices design.

• Implement logging, metrics, and observability for AI systems.

• Track model performance and system reliability in production environments.

• Work closely with product managers, engineers, and data scientists.

Requirements:

• 5+ years of programming skills in one or more modern languages (such as Python, Java, Go, or similar).

• Experience building backend services and APIs.

• Experience integrating machine learning models or LLMs into applications.

• Understanding of microservices architecture and distributed systems.

• Experience with Docker and containerized applications.

• Familiarity with Kubernetes or cloud infrastructure.

• Experience working with databases and data processing pipelines.

Preferred Qualifications:

• Experience building LLM-based applications.

• Experience with RAG architectures and embeddings.

• Experience with vector databases or semantic search systems.

• Familiarity with model serving frameworks or inference platforms.

• Experience working in production AI environments.

Strong Advantage:

• Experience working with local or self-hosted AI models (e.g., Llama, Mistral, or similar).

• Experience deploying AI models in on-premise or private cloud environments.

• Familiarity with running LLM inference locally using frameworks such as Ollama, vLLM, or Hugging Face Transformers.

• Experience optimizing models for GPU/CPU inference and resource-constrained environments.