Copy of AI Engineer

Quantifi•New York, NY

About The Position

Quantifi is a leading provider of analytics, trading, and risk management solutions for the global financial industry. For over two decades, we have partnered with banks, asset managers, hedge funds, and other financial institutions to deliver innovative, high-performance technology recognized for its accuracy, speed, and deep domain expertise. Our culture combines technical excellence with a strong focus on client success, empowering teams to solve complex problems and make better decisions. Now, we are building an AI-native platform to redefine how teams work and make decisions. We are harnessing cutting-edge AI capabilities to enhance our operations and expand into broader product use cases, all supported by scalable, high-performance infrastructure. As our first AI Engineer, you will play a pivotal role in architecting, building, and deploying the core systems that form Quantifi’s AI foundation. Your work will directly shape how AI is embedded across the company, influencing both our current solutions and our long-term strategic vision.

Requirements

Bachelor's degree in Computer Science, Engineering or a related field
3+ years of experience as a software or platform engineer, building and deploying production systems with Python, TypeScript, or Node.js.
Solid understanding of AI/ML fundamentals, with hands-on experience using LLMs and building, deploying, and operating AI agents.
Experience with data pipelines, retrieval systems, or other backend infrastructure that supports AI applications.
Familiarity with distributed systems concepts (scalability, performance optimization, cost management), and AI-specific techniques including agent orchestration, prompt engineering, and intelligent routing logic.
Ability to work across the full development lifecycle - from architecture and prototyping to deployment and monitoring - in a fast-moving environment.
Strong problem-solving skills, with the ability to navigate ambiguity and adapt to evolving requirements.

Nice To Haves

Experience with agent frameworks such as LangChain, LangGraph, or CrewAI
Experience with Microsoft ecosystem tools, including C# and Azure AI services (e.g., Azure OpenAI, Copilot).
Background with vector databases like Pinecone, Weaviate, Qdrant, or similar tools.
Familiarity with Claude Enterprise or other secure LLM environments.
Experience designing agent-based architectures or internal developer platforms.
Exposure to RevOps, GTM tooling, or enterprise SaaS systems.
Proficiency in additional backend languages such as Go or Java.

Responsibilities

Own the full lifecycle of AI-powered agents and workflows - from initial design through deployment - starting with existing solutions and evolving toward custom systems.
Build and maintain data flows and retrieval infrastructure - including the Model Context Protocol - to transform raw business data into structured, policy-compliant formats and enable secure, semantic access across domains like sales, support, and product.
Lead the evolution of the agent orchestration layer, enabling intelligent task routing across multiple LLMs/Agents to optimize scalability, cost, latency, and throughput in large-scale production AI systems.
Implement observability and feedback mechanisms to measure agent performance, identify areas for optimization, capture trust signals, and guide continuous improvement.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Quantifi.
Stay informed on emerging approaches in AI agent architectures, orchestration frameworks, and retrieval-augmented systems to continuously refine our platform design and strategy.