AI Engineer

Our company is seeking an experienced AI Engineer to architect and build our AI Assistant and Agent infrastructure from the ground up. This is a unique opportunity to design and implement production-grade RAG (Retrieval-Augmented Generation) systems and autonomous AI agents that will power intelligent solutions.

Key Responsibilities

AI Infrastructure & Architecture

• Design and implement scalable RAG systems using modern LLM frameworks and vector databases
• Build end-to-end AI Assistant infrastructure supporting multiple use cases and user personas
• Develop autonomous AI Agent systems with tool-use capabilities, memory management, and multi-step reasoning
• Work with data engineers to create robust data pipelines for ingesting, processing, and embedding enterprise data sources
• Implement vector search and semantic retrieval systems optimized for accuracy and latency
• Create monitoring, observability, and evaluation frameworks for AI system performance

LLM Operations & Optimization

• Implement prompt engineering strategies and evaluation frameworks
• Build context management systems to optimize token usage and response quality
• Develop guardrails, content filtering, and safety mechanisms
• Optimize inference pipelines for cost, latency, and throughput

Required Qualifications

• 3 years of software engineering experience with production systems
• Hands-on experience building RAG systems using LLMs (OpenAI, Anthropic, or similar)
• Experience with LLM frameworks such as LangChain, LlamaIndex, or similar
• Proven ability to architect and build AI systems from concept to production
• Strong understanding of asynchronous programming and event-driven systems
• Familiarity with AWS cloud services (Lambda, ECS, S3, etc.)
• Strong problem-solving skills and ability to work independently
• Excellent communication skills for technical discussions and documentation

Preferred Qualifications

• Experience with vector databases (Pinecone, Weaviate, Qdrant, Chroma, pgvector, etc.)
• Knowledge of AI Agent frameworks (AutoGPT, LangGraph, CrewAI, etc.)
• Experience with embedding models and semantic search optimization
• Familiarity with streaming LLM responses and real-time interfaces
• Understanding of prompt engineering and few-shot learning techniques
• Experience with model evaluation and performance monitoring
• Knowledge of AWS Bedrock, SageMaker, or other ML services
• Background in healthcare technology or regulated industries
• Experience with HIPAA-compliant systems and data handling