Sr. AI Engineer - Large Language Models Agentic Systems

Role overview

Responsibilities

• check_circle Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python
• check_circle Design and implement retrieval-augmented generation (RAG) pipelines over enterprise datasets using embeddings and vector databases
• check_circle Build and orchestrate multi-step, tool-using AI agents (planning, execution, and memory) using frameworks such as LangChain or LangGraph
• check_circle Integrate AI solutions with APIs, backend systems, and cloud platforms to enable scalable deployment
• check_circle Establish evaluation, reliability, and performance strategies, including accuracy, latency, and cost optimization

Basic qualifications

• Strong expertise in Python, with experience building and deploying production-grade backend systems
• Hands-on experience developing applications using large language models, including prompt engineering and orchestration
• Proven experience designing and implementing RAG architectures, including embeddings and vector databases
• Experience with agentic frameworks such as LangChain, LangGraph, or similar technologies
• Strong system design skills with experience building and scaling cloud-based applications

Preferred qualifications

• Experience working with enterprise-scale data and deploying AI solutions in production environments
• Familiarity with multiple LLM providers and model optimization techniques
• Knowledge of evaluation frameworks for LLM performance and responsible AI practices
• Experience building distributed systems or microservices architectures
• Exposure to MLOps, CI/CD pipelines, and monitoring of AI systems

Benefits

• check_circle Medical/Dental/Vision/Life Insurance
• check_circle Paid holidays plus Paid Time Off
• check_circle 401(k) plan and contributions
• check_circle Long-term/Short-term Disability
• check_circle Paid Parental Leave
• check_circle Employee Stock Purchase Plan