Agentic AI, Engineer

Role Overview

Masterworks is seeking an Agentic AI Engineer to design, build, and deploy agentic AI systems that can plan, reason, and act. The role is based at the company HQ.

Role Purpose

To architect and operationalize agentic AI systems—both single-agent and multi-agent—that integrate foundation models with enterprise systems, tools, and APIs, transforming generative AI into reliable, goal-driven solutions capable of solving complex real-world business problems.

Key Responsibilities

Architecture & Design

• Architect, build, and deploy agentic AI systems that integrate AI agents with foundation models, enterprise systems, third-party tools, and APIs using established agentic frameworks or custom-built orchestrators.
• Design single-agent and multi-agent workflows, including planning, delegation, tool selection, handoffs, inter-agent communication, and human-in-the-loop controls.

Data & Reasoning

• Build and maintain retrieval-augmented generation (RAG), memory, and reasoning pipelines that ground agent decisions in reliable, real-world data and enable persistent, contextual, and adaptive behavior.

Performance & Optimization

• Optimize orchestration and reasoning performance while balancing autonomy, latency, cost, interpretability, reliability, and maintainability.

Monitoring & Evaluation

• Monitor, evaluate, and benchmark agent performance, and help ensure AI systems are safe, accurate, trustworthy, observable, and capable of delivering a high-quality user experience.

Documentation & Knowledge

• Document agent architectures, communication flows, guardrails, context-engineering strategies, memory design, tool interfaces, and orchestration logic to ensure clarity and reproducibility.
• Stay current with advances in agentic AI, multi-agent orchestration, RAG, model-context protocols, cognitive architectures, evaluation methods, and AI safety mechanisms.

Collaboration & Delivery

• Collaborate with Generative AI engineers, application engineers, MLOps engineers, and product teams to move agentic AI solutions from prototype to production.
• Collaborate with cross-functional teams to design and deliver complete AI solutions for customers.

Qualifications & Experience

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field.
• 2+ years of hands-on experience developing agentic AI systems, LLM-powered applications, or advanced Generative AI solutions.
• Preferably 5+ years of overall professional software engineering experience.
• Contributions to open-source agentic AI frameworks, orchestration platforms, evaluation tooling, or agent communication protocols.
• Experience building microservices and deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
• Experience with AI safety, guardrails, observability, traceability, evaluation, and explainability for agentic AI systems.
• Experience deploying LLM or agentic workloads in production using containers, Kubernetes, CI/CD pipelines, and modern MLOps or LLMOps practices.