AI Engineer
First seen by Alion on Sep 30, 2026.
AI Engineer
Role Overview :
We are looking for an experienced AI Engineer with strong hands-on expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and cloud platforms such as AWS, Azure or GCP.
The ideal candidate will be responsible for designing, developing and deploying AI-powered solutions, with a strong focus on Generative AI, LLM applications and scalable cloud-based AI systems.
Key Responsibilities :
- Design, develop and deploy AI/ML and Generative AI solutions for enterprise use cases.
- Build and implement LLM-powered applications using modern Generative AI frameworks and techniques.
- Develop RAG pipelines for enterprise knowledge retrieval and question-answering applications.
- Work with embeddings, vector databases, semantic search and document retrieval systems.
- Develop scalable AI applications and services using Python.
- Integrate LLMs with existing applications, APIs, data platforms and enterprise systems.
- Design and implement prompt engineering, context management and evaluation strategies.
- Deploy AI/ML solutions on AWS, Azure or GCP.
- Build production-ready AI services with appropriate monitoring, logging and performance optimisation.
- Collaborate with Data Scientists, ML Engineers, Data Engineers and product teams to translate business requirements into AI solutions.
- Evaluate LLM performance, response quality, latency and cost, and continuously optimise AI solutions.
- Stay updated with emerging developments in Generative AI, LLMs, RAG and AI engineering.
Required Skills :
- Strong hands-on experience with Python.
- Experience building Generative AI / AI applications.
- Strong understanding of LLMs and their practical implementation.
- Hands-on experience developing RAG-based applications.
- Knowledge of embeddings, vector databases and semantic search.
- Experience with at least one major cloud platform : AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Strong understanding of APIs, microservices and cloud-based application development.
- Experience with AI/ML model integration and deployment.
- Good understanding of software engineering principles, version control and development best practices.
Good to Have :
- Experience with frameworks such as LangChain, LlamaIndex or similar.
- Exposure to OpenAI, Azure OpenAI, Anthropic, Gemini or other LLM platforms.
- Experience with vector databases such as Pinecone, FAISS, Weaviate, Milvus or similar.
- Knowledge of Docker and Kubernetes.
- Experience with CI/CD and cloud-native deployments.
- Exposure to Agentic AI and AI agents.
- Experience with LLM evaluation, observability and responsible AI practices.
Key Competencies :
- Strong analytical and problem-solving skills.
- Ability to design scalable and production-ready AI solutions.
- Strong understanding of emerging Generative AI technologies.
- Ability to work collaboratively with cross-functional teams.
- Strong communication and technical documentation skills
Skills
Python, Generative AI, LLM, RAG, AWS, LangChain, Artificial Intelligence, Prompt Engineering, Agentic AI