Generative AI Engineer - LLM/RAG
First seen by Alion on Oct 26, 2026.
Key Responsibilities :
- Design, develop, and deploy Generative AI applications using LLMs and modern AI frameworks.
- Build and optimize RAG-based solutions to enable context-aware information retrieval and generation.
- Develop AI agents and agentic AI workflows to automate complex tasks and business processes.
- Implement effective prompt engineering techniques to improve model accuracy, relevance, and response quality.
- Develop AI-powered applications, chatbots, virtual assistants, and intelligent automation solutions.
- Integrate LLMs, APIs, vector databases, and external data sources into AI applications.
- Evaluate model performance, troubleshoot issues, and optimize AI solutions for accuracy, scalability, and reliability.
- Collaborate with cross-functional teams and stakeholders to understand requirements and deliver effective AI solutions.
- Stay updated on emerging Generative AI technologies, frameworks, tools, and industry best practices.
Required Skills & Qualifications :
- Strong programming and coding proficiency in Python is mandatory.
- Strong understanding of Generative AI concepts and Large Language Models (LLMs).
- Hands-on knowledge of Retrieval-Augmented Generation (RAG) and semantic search.
- Understanding of AI agents, agentic AI architectures, and multi-step AI workflows.
- Knowledge of prompt engineering techniques and LLM application development.
- Familiarity with APIs, data processing, and integrating AI models into applications.
- Strong analytical, problem-solving, and debugging skills.
- Ability to learn new technologies quickly and work in a collaborative environment.
Skills
Artificial Intelligence, Python, Generative AI, Agentic AI, RAG, Prompt Engineering, Conversational AI, AI Integration, LLM