Applied AI Engineer

About the Role

We are looking for an Applied AI Engineer to design build and deploy intelligent AI solutions that solve real business this role youll work with Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) GraphRAG AI agents and knowledge graphs to create scalable production-ready AI applications.

This is an AI-first engineering role where leveraging AI development tools such as ChatGPT Cursor GitHub Copilot Claude or Windsurf is an essential part of the development workflow.

Key Responsibilities

• Design develop and deploy AI-powered applications using LLMs.
• Build and optimize RAG and GraphRAG pipelines.
• Develop AI agents and multi-agent workflows for business automation.
• Design and manage knowledge graphs using GraphDB technologies.
• Integrate enterprise data sources with AI applications.
• Engineer prompts workflows and agent orchestration for reliable AI systems.
• Evaluate and optimize AI models for quality latency scalability and cost.
• Build production-ready APIs and AI services.
• Collaborate with cross-functional teams to deliver AI-driven products.
• Stay up to date with the latest AI models frameworks and best practices.

Requirements

• Bachelors degree in Computer Science Software Engineering AI or a related field.
• 3 years of experience developing AI-powered or data-intensive applications.
• Strong proficiency in Python.
• Hands-on experience with LLMs (OpenAI Azure OpenAI Anthropic Gemini or similar).
• Experience implementing Retrieval-Augmented Generation (RAG).
• Experience with Graph Databases such as Neo4j Amazon Neptune Memgraph or GraphDB.
• Familiarity with vector databases such as Pinecone Qdrant Weaviate Milvus or pgvector.
• Experience integrating AI models through APIs and SDKs.
• Solid understanding of REST APIs Git Docker and cloud platforms (Azure AWS or GCP).
• Strong analytical debugging and problem-solving skills.

Preferred Qualifications

• Experience with GraphRAG architectures.
• Knowledge of AI agent frameworks such as LangGraph CrewAI AutoGen Semantic Kernel or OpenAI Agents SDK.
• Experience with Model Context Protocol (MCP).
• Prompt engineering and AI evaluation frameworks.
• Knowledge of semantic search and hybrid retrieval.
• Experience with FastAPI Django or Flask.
• Familiarity with Kubernetes CI/CD pipelines and microservices.
• Experience building knowledge graphs and ontology design.

What We Offer

• Opportunity to build cutting-edge AI products.
• Collaborative and innovative engineering environment.
• Exposure to the latest AI technologies and frameworks.
• Professional growth and continuous learning opportunities.
• Competitive salary and benefits package.

Join Our Team

If youre passionate about building practical AI applications enjoy working with the latest AI technologies and thrive in an AI-first development environment wed love to hear from you!