AI Engineer (Jr/Sr)
Summary
AI Engineer building generative-AI applications end to end: LLM apps, RAG pipelines, and agentic workflows (MCP tools, vector search, prompt engineering) from PoC through deployment and support. Core stack is Python, LLM providers (Azure OpenAI/OpenAI/Claude/Gemini), and agent frameworks like LangChain/LangGraph, plus REST APIs, SQL, and CI/CD.
About the role
Develop and enhance AI/Generative AI applications using Large Language Models (LLMs). Design and implement RAG pipelines for intelligent knowledge retrieval and question-answering solutions. Build AI agents and agentic workflows for reasoning, planning, tool usage, and task automation. Develop end-to-end AI solutions from PoC and prototyping through implementation, testing, deployment, and support.
Key responsibilities
Develop and enhance AI/Generative AI applications using Large Language Models (LLMs)
Design and implement RAG pipelines for intelligent knowledge retrieval and question-answering solutions
Build AI agents and agentic workflows for reasoning, planning, tool usage, and task automation
Develop and integrate MCP tools to connect AI applications with enterprise systems, databases, APIs, and engineering services
Develop end-to-end AI solutions from PoC and prototyping through implementation, testing, deployment, and support
Integrate AI capabilities with APIs, databases, backend services, and engineering applications
Work with prompt engineering, embeddings, vector databases, and semantic search to improve AI solution quality
Evaluate, test, debug, and optimize AI solutions for accuracy, reliability, performance, and scalability
Apply good software engineering practices including version control, testing, documentation, and CI/CD
Collaborate with cross-functional teams to translate business and engineering requirements into practical AI solutions
About you
Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Computer Engineering, or a related field
At least 2-6 years of related working experience
Hands-on experience developing AI/Generative AI solutions, such as LLM applications, RAG systems, AI agents, or AI-driven automation
Strong programming skills in Python
Good understanding of LLMs, RAG, Agentic AI, prompt engineering, embeddings, and vector databases
Experience with REST APIs, backend development, databases, and system integration
Familiarity with SQL, Git/GitHub, testing, debugging, and software development lifecycle practices
Strong analytical, problem-solving, and troubleshooting skills
Experience with Azure OpenAI, OpenAI, Claude, Gemini, or open-source LLMs
Experience with LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar Agentic AI frameworks