Middle AI Engineer

We are looking for a Middle AI Engineer to design, build, and integrate AI-powered features into real production systems.

This role focuses on the practical application of AI, primarily LLM-based solutions, conversational systems, automation, and AI integrations within existing products and platforms.
The ideal candidate is not a researcher, but a hands-on engineer who delivers AI features that solve real business problems.

Key Responsibilities

• Design and implement AI-powered features for SaaS platforms, internal tools, and customer-facing products

• Build and integrate LLM-based solutions (chatbots, copilots, assistants, content generation)

• Implement prompting strategies, RAG pipelines, and vector search

• Integrate AI capabilities into existing systems (CRM, ERP, CMS, web platforms)

• Develop and maintain AI backend services (APIs, microservices)

• Work closely with product and business stakeholders to translate requirements into AI solutions

• Ensure performance, reliability, and security of AI integrations

• Optimize cost, latency, and output quality

• Support MVPs through production-ready deployments

Core Technical Skills (Must-Have) AI / LLM

• Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, etc.)

• Prompt engineering and prompt optimization

• Retrieval-Augmented Generation (RAG)

• Vector databases (Pinecone, FAISS, Weaviate, Qdrant)

• Evaluation of AI outputs (quality control, hallucination mitigation)

Backend Engineering

• Strong proficiency in Python

• Experience building REST / GraphQL APIs

• Integrating AI into backend services

• Familiarity with async processing and job queues

Cloud & Infrastructure

• Hands-on experience with AWS, Azure, or GCP

• Understanding of basic MLOps concepts (monitoring, versioning, lifecycle)

• Containerization (Docker) is a plus

Nice-to-Have Skills

• Experience with JavaScript / Node.js / .NET / PHP systems

• Frontend awareness (React / Vue) for AI feature integration

• Knowledge of data pipelines and ETL processes

• Experience with no-code / low-code AI tools

• Exposure to regulated domains (healthcare, finance) is a plus