168. Senior AI Engineer - LLM and Agent Systems

About the role

AI Engineer with hands-on experience in building production-grade artificial intelligence systems using large language models (LLMs), agentic frameworks, and modern data infrastructure. The ideal candidate designs, develops, and deploys intelligent applications that leverage LLM orchestration, retrieval-augmented generation (RAG), and memory-managed architectures.

Responsibilities

• Design and implement agentic workflows using LangGraph and LangChain, including multi-step reasoning, tool usage, and human-in-the-loop patterns.
• Integrate LLMs (OpenAI, Anthropic, Google Vertex AI, open-source models) via REST APIs and SDKs into scalable backend services.
• Build and maintain RESTful APIs (FastAPI) to serve AI-powered functionality to frontends and external consumers.
• Architect and manage vector database solutions (Milvus) for semantic search and retrieval-augmented generation (RAG).
• Design context engineering strategies, including prompt templates, dynamic context window management, token optimization, and context compression techniques.
• Implement short-term memory (conversational buffers, sliding windows, summary memory) and long-term memory (persistent vector stores, knowledge graphs, user profile stores) using MongoDB and vector databases.
• Store and manage structured and unstructured data in MongoDB, designing schemas that support conversation history, user state, and agent checkpoints.
• Evaluate and improve the quality of LLM responses through prompt engineering, few-shot examples, guardrails, and automated evaluation pipelines.
• Collaborate with DevOps teams to containerize and deploy AI services using Docker, Kubernetes, and CI/CD pipelines on AWS or GCP.
• Required Qualifications
• Strong command of Python (3+ years)
• Demonstrable experience with LangChain and LangGraph (graph-based agent orchestration, state management, conditional edges, parallel execution).
• Solid understanding of the fundamentals of LLMs: tokenization, embeddings, temperature/sampling, RAG.
• Hands-on experience with vector databases and embedding models for semantic search and retrieval pipelines.
• Experience designing and consuming REST APIs; knowledge of authentication.
• Proficiency in MongoDB (document modeling, aggregation pipelines, indexing strategies).
• Understanding memory architectures for conversational AI: summary memory, entity memory, and long-term persistent stores.
• Familiarity with context engineering: token budget management, hybrid search (sparse + dense).
• English level: B2 or higher

Requirements

• Experience with assessment frameworks (RAGAS, Langfuse (LangSmith), customized assessments).
• Experience with streaming responses.

Benefits

Additional Information

We're looking for a Senior AI Engineer - LLM and Agent Systems to join Source Meridian About Source Meridian Source Meridian is a development software company that works to solve the industry's most challenging problems in healthcare practices. We are laser focused on specific technologies in the healthcare and life science industries: Healthcare technology, artificial intelligence, and healthcare interoperability.

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