AI Engineer – RAG & Agentic AI

Job Overview

Key Responsibilities

• Design, develop, and deploy scalable Generative AI and LLM-powered applications.
• Build end-to-end Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, preprocessing, chunking, embedding, retrieval, context management, and response generation.
• Develop and optimize prompt engineering strategies for accuracy, relevance, reliability, and consistent model behavior.
• Design and implement agentic AI solutions capable of reasoning, tool calling, task orchestration, and multi-step workflows.
• Work with LLMs such as GPT-4, Claude, and other foundation models to develop enterprise AI capabilities.
• Integrate LLMs with enterprise APIs, databases, business applications, and external services.
• Develop AI services and supporting backend components using Python, Java, or Node.js.
• Build APIs and application integrations using JSON, REST, and other modern integration technologies.
• Develop scalable frontend experiences using React and JavaScript for AI-powered applications where required.
• Work with SQL databases to retrieve, analyze, and integrate structured enterprise data into AI workflows.
• Design reusable AI components, frameworks, and services that can be leveraged across multiple use cases.
• Implement appropriate evaluation, testing, monitoring, and optimization mechanisms for AI applications.

Required Skills & Experience

• 6+ years of software engineering and application development experience.
• Strong hands-on experience in AI Engineering / Generative AI / LLM application development.
• Proven experience building RAG pipelines and LLM-powered applications.
• Strong knowledge of Prompt Engineering and LLM optimization techniques.
• Hands-on experience with Agentic AI development, AI agents, tool calling, workflow orchestration, or multi-step reasoning.
• Experience working with GPT-4, Claude, or comparable LLM platforms.
• Strong programming experience in Python and at least one enterprise programming language such as Java, C#, or Node.js.
• Good experience with JavaScript and React.
• Strong understanding of REST APIs, JSON, SQL, and enterprise integrations.
• Ability to design scalable, maintainable, and secure AI-enabled applications.
• Strong problem-solving, analytical, communication, and collaboration skills.

Technology Stack

• AI/GenAI: RAG, Prompt Engineering, Agentic AI, GPT-4, Claude, LLMs
• Languages: Python, Java, JavaScript, C, Swift, .NET, Node.js
• Frontend: React
• Data & Integration: SQL, JSON, REST APIs
• Application Development: Enterprise APIs, AI-powered applications, workflow orchestration

Good to Have

• Experience with vector databases and embedding technologies.
• Knowledge of RAG evaluation, LLM observability, and AI application testing.
• Experience with LangChain, LangGraph, Semantic Kernel, or similar AI frameworks.
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and CI/CD.
• Understanding of AI security, responsible AI, data privacy, and enterprise governance.

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related technical discipline.

Key Competencies

• Generative AI | RAG Pipelines | Prompt Engineering | Agentic AI | GPT-4 | Claude | Python | Java | JavaScript | React | .NET | Node.js | SQL | JSON | REST APIs