Applied AI Engineer
First seen by Alion on Sep 18, 2026.
Job Summary :
We are looking for a skilled AI / LLM Engineer with hands-on experience in Generative AI, Prompt Engineering, and Large Language Model (LLM) application development. The ideal candidate should have expertise in building AI-powered solutions using leading LLM APIs, orchestrating workflows, processing unstructured data, and deploying scalable AI pipelines on cloud platforms.
Key Responsibilities :
- Design, develop, and optimize prompt engineering strategies for LLM-based applications.
- Build and maintain Generative AI solutions using leading LLM APIs such as OpenAI, Anthropic, and similar platforms.
- Develop AI workflows and Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain and LlamaIndex.
- Process and analyze structured and unstructured data using Python, Pandas, and NumPy.
- Build document intelligence and NLP solutions for extracting, transforming, and analyzing information from various data sources.
- Implement vector search and embedding solutions using vector databases such as FAISS, Pinecone, ChromaDB, or similar technologies.
- Design AI evaluation frameworks to measure model quality, reliability, and performance.
- Develop mechanisms for hallucination detection, drift monitoring, confidence scoring, and AI output validation.
- Work with human-in-the-loop (HITL) systems and annotation workflows to continuously improve model accuracy.
- Build, deploy, and maintain AI pipelines and REST APIs in cloud environments.
- Collaborate with cross-functional teams to integrate AI solutions into enterprise applications.
- Follow best practices for code quality, version control, CI/CD, and scalable AI deployment.
Required Skills & Qualifications :
- Experience in AI/ML, NLP, or Generative AI application development.
- Strong experience in Prompt Engineering and LLM-based application development.
- Hands-on experience with LLM APIs such as OpenAI, Anthropic, or similar platforms.
- Proficiency in Python and data processing libraries including Pandas and NumPy.
- Experience with LangChain, LlamaIndex, or equivalent AI orchestration frameworks.
- Strong understanding of NLP, document intelligence, and unstructured data processing.
- Experience with vector databases and embedding models (FAISS, Pinecone, Weaviate, ChromaDB, Milvus, etc.).
- Knowledge of AI evaluation methodologies, hallucination detection, drift monitoring, and confidence scoring.
- Experience building AI pipelines, APIs, and cloud-native applications.
- Familiarity with AWS, Azure, or GCP cloud platforms.
- Working knowledge of Git, CI/CD pipelines, and software development best practices.
Preferred Qualifications :
- Experience with Retrieval-Augmented Generation (RAG) architectures.
- Exposure to MLOps, model monitoring, and AI governance frameworks.
- Experience with annotation tools and human feedback loops for model improvement.
- Knowledge of containerization technologies such as Docker and Kubernetes is an added advantage.
- Excellent analytical, problem-solving, and communication skill
Skills
Artificial Intelligence, LLM, OpenAI, Prompt Engineering, Generative AI, RAG, LangChain, LangGraph, NLP, Python, MLOps