AI Agent Engineer | W2 Only

Job Summary We are seeking a highly skilled AI Agent Engineer with a strong background in AI engineering, data proficiency, and AIOps. The ideal candidate will have experience building and deploying production-level AI solutions, developing intelligent agents, and applying AI to enhance IT operations. This role requires both hands-on technical expertise and the ability to communicate insights effectively to drive business outcomes. Key Responsibilities AI Agent Development: • Design, build, and deploy advanced AI agents and workflows using modern frameworks such as LangChain, LangGraph, and LangFlow. • Optimize agent architecture for scalability, efficiency, and reliability in production environments. Data Proficiency: • Write and optimize complex SQL queries for relational databases (e.g., Oracle). • Manage and query large-scale datasets across both SQL and NoSQL databases (e.g., Cassandra). Data Analysis & Visualization: • Perform deep data analysis to uncover trends, patterns, and actionable insights. • Develop and present compelling data stories using visualization tools to support strategic decision-making. AIOps & Observability: • Implement AIOps solutions to automate IT operations and improve system performance. • Work with observability and monitoring tools such as Kibana, New Relic, and related platforms to ensure system health and operational efficiency. Required Skills & Qualifications • 10+ years of IT experience, including 4+ years in AI Ops. • 3–7 years of hands-on experience building and deploying AI solutions in production environments. • Strong proficiency in LangChain, LangGraph, LangFlow, or similar AI frameworks. • Expertise in SQL and hands-on experience with NoSQL databases. • Strong analytical, problem-solving, and data storytelling skills. • Experience with AIOps platforms and observability tools (Kibana, New Relic). • Excellent communication and collaboration skills with cross-functional teams. Preferred Qualifications • Experience with cloud-based AI/ML platforms (AWS, Azure, or GCP). • Knowledge of MLOps pipelines and CI/CD for AI workflows. • Familiarity with other monitoring/observability tools and practices.