Applied AI Engineer

About the Opportunity

We’re looking for an Applied AI Engineer to turn advances in artificial intelligence into software that people can use in their daily work. You’ll develop intelligent applications, build autonomous agent systems, and create the infrastructure needed to move AI projects from early experiments into dependable production services.

This is a software engineering role with a strong focus on practical AI development. You’ll work with large language models (LLMs), agent orchestration, retrieval systems, and developer tools while collaborating with teams across a technology-intensive financial environment.

What You’ll Build

AI Agents and Intelligent Applications

• Design and deploy AI agents capable of completing multistep tasks using external tools and application data.
• Build user-facing applications that bring AI capabilities into existing business and engineering workflows.
• Develop agent orchestration systems that coordinate tasks, manage execution, and handle failures.
• Implement memory, context management, and reasoning workflows for more capable AI applications.
• Connect language models to APIs, databases, and internal services.
• Take new AI products from initial concept through testing, deployment, and ongoing improvement.

AI Infrastructure and Reusable Frameworks

• Create shared components that simplify AI application development across engineering teams.
• Develop reusable agent tools, capabilities, and integration frameworks.
• Build large-scale information retrieval systems that help AI applications access relevant data.
• Improve the infrastructure used to run, evaluate, and maintain AI-powered services.
• Develop data integrations that connect AI systems with existing software platforms.
• Identify opportunities to make AI applications more scalable, reliable, and maintainable.

Experimentation and Developer Productivity

• Evaluate new language models, agent frameworks, and approaches to AI-assisted software development.
• Experiment with AI coding agents and tools that improve engineering productivity.
• Build prototypes to test technical ideas before committing to larger implementations.
• Measure application behavior, investigate unexpected outputs, and refine system performance.
• Turn successful experiments into production-ready tools and services.

Required Skills and Qualifications

Software Engineering and Production AI

• Extensive experience designing, developing, and maintaining software applications.
• Demonstrated ability to build and scale AI-powered systems in production environments.
• Hands-on experience with agentic AI frameworks, orchestration, and tool integration.
• Strong understanding of software architecture, backend services, and system integrations.
• Experience developing applications that coordinate multiple steps, maintain context, and interact with external tools.
• Ability to move quickly from a technical idea to a working prototype and production implementation.
• Strong analytical skills and a record of delivering technically challenging projects.

Relevant AI Technologies

Experience with the following concepts is especially relevant:

• Large language models: Model integration, experimentation, and application development.
• Agentic AI: Task orchestration, tool calling, memory, and multistep reasoning.
• Retrieval systems: Information indexing, search, and retrieval-augmented generation (RAG).
• AI developer tools: Coding agents, automated engineering workflows, and reusable AI capabilities.
• Data integration: Connecting AI applications to structured and unstructured information sources.
• Production engineering: Scaling applications, troubleshooting failures, and improving operational reliability.

Education and Professional Strengths

• A bachelor’s degree in any academic discipline.
• Strong professional or academic achievement.
• Ability to work independently on complex, loosely defined technical problems.
• Clear communication skills and a collaborative approach to engineering.
• Initiative, sound technical judgment, and comfort taking responsibility for new projects.

Engineering Environment and Project Ownership

You’ll work on AI applications at different stages of maturity, from exploratory prototypes to systems used in everyday operations. Some projects will involve creating entirely new capabilities, while others will focus on making existing tools more useful through intelligent automation.

What to Expect

• End-to-end development: Own technical work from early experimentation through production deployment.
• Agent-focused engineering: Build systems that combine language models, external tools, and application-specific logic.
• Shared infrastructure: Develop frameworks and services that other engineering teams can reuse.
• Cross-functional collaboration: Work with internal teams to understand their workflows and identify valuable AI applications.
• Rapid iteration: Test ideas, evaluate results, and adjust implementations as AI technologies evolve.
• Technical independence: Make architectural decisions and solve unfamiliar problems without relying on a fixed implementation playbook.

Why Consider This Applied AI Engineering Role?

This opportunity combines advanced AI application development with the broader challenges of production software engineering. Rather than focusing exclusively on model experimentation, you’ll build systems that connect AI capabilities to practical tasks and existing technology.

• Develop autonomous agents and intelligent applications used by internal teams.
• Work with modern language models, retrieval architectures, and AI coding tools.
• Build reusable frameworks that support multiple AI initiatives.
• Contribute to projects involving complex data and sophisticated software environments.
• Take ownership of new technical ideas and turn them into working applications.

This position is suited to an experienced software engineer who has already built production AI systems and wants to work on more ambitious applications involving agentic workflows, shared AI infrastructure, and intelligent software automation.