AI Engineer
Remote • Remote US
Posted 6mo ago
About the job
CoreStory unlocks the hidden intelligence in legacy code by using AI to surface business logic and technical insights, enabling enterprises to modernize faster and reduce risk. We are seeking an AI Engineer passionate about building intelligent systems that integrate large language models, retrieval architectures, and conversational agents into scalable products. This role is central to the AI engine powering the CoreStory Platform, focusing on developing and optimizing LLM integration, vector search systems, prompt orchestration, agentic systems, and retrieval-augmented generation (RAG) pipelines. You will collaborate with product, data, and infrastructure teams to prototype, productionize, and evolve our AI stack, ensuring accuracy, explainability, efficiency, and cutting-edge capabilities.
Responsibilities
- Design, implement, and optimize LLM-powered systems like RAG, chat agents, summarizers, and knowledge graph integration.
- Build and manage data indexing and retrieval pipelines using frameworks such as LlamaIndex or LangChain.
- Implement and maintain vector databases including Pinecone, Neo4j, Weaviate, Chroma, or Azure Cognitive Search.
- Integrate open-source and proprietary LLMs (e.g., GPT, Claude, Llama) into the platform.
- Develop and refine AI-driven features such as generative insights, automated summarization, and narrative analytics.
- Collaborate with DevOps and backend teams to deploy scalable AI services.
- Benchmark model performance, latency, and cost, identifying optimization opportunities.
- Stay current with AI advancements and propose innovative applications.
- Contribute to internal documentation, experimentation frameworks, and evaluation methodologies.
Requirements
- 7+ years of overall engineering experience, with at least 3+ years in AI engineering, machine learning, or applied NLP.
- Strong hands-on experience with LlamaIndex, LangChain, or similar orchestration frameworks.
- Experience designing and implementing vector database solutions (e.g., Pinecone, Neo4j, FAISS, Milvus, Weaviate).
- Solid understanding of LLM APIs (OpenAI, Anthropic, Mistral, Hugging Face, etc.).
- Proficiency in Python, with experience in libraries like FastAPI, Pandas, or NumPy.
- Understanding of retrieval-augmented generation (RAG) patterns, embeddings, and tokenization.
- Familiarity with prompt engineering, tool calling, and chat agent architectures.
- Strong problem-solving and analytical mindset focused on performance and scalability.
- Demonstrated interest in staying up-to-date with the AI landscape.
- Experience deploying AI services in production (e.g., using Docker, Azure, or AWS).
- Exposure to LangGraph, semantic search, or hybrid RAG systems.
- Familiarity with knowledge graphs, document intelligence, or multimodal AI.
Benefits
- Competitive compensation and equity
- Flexible, remote-first work environment
- Opportunities to define and build the AI roadmap
- Collaborative, learning-oriented culture
- Access to cutting-edge AI models, research, and infrastructure