Senior Applied AI Engineer

About the role

Job Description

A growing fintech company focused on modern financial services and trading technology is looking for a Senior Applied AI Engineer to build secure, production-grade AI applications supporting financial services workflows. The company combines financial services expertise with advanced data, AI, and engineering capabilities, with a strong focus on security, auditability, correctness, and reliability. The engineering environment is primarily built around the Microsoft Azure ecosystem and integrates closely with .NET-based enterprise systems and sensitive financial data.

As a Senior Applied AI Engineer, you'll focus on turning emerging AI capabilities into reliable applications that can be deployed and used in real-world financial workflows. You'll build AI-powered applications using C#, .NET, and Azure while designing and implementing RAG pipelines, agentic workflows, and LLM integrations. This is a hands-on engineering position focused on integrating AI into production systems through APIs, function calling, tool orchestration, and enterprise system integrations rather than model training or fundamental AI research.

You'll work across the application and AI stack to develop backend services and APIs that expose AI capabilities while implementing the guardrails, validation, observability, and human-in-the-loop workflows required for production financial applications. Working closely with Product, Data, Platform, and AI teams, you'll help transform AI prototypes into secure, scalable, and dependable products that can operate within enterprise and regulated environments.

The ideal candidate is a strong software engineer who has developed production applications and has hands-on experience applying generative AI, LLMs, RAG, and agent workflows to real-world problems. You'll have the opportunity to work with technologies including Azure OpenAI, Azure AI Search, AKS, Azure Functions, Service Bus, Cosmos DB, and modern AI orchestration frameworks while helping define how AI can be integrated into critical financial services workflows.

Required Skills & Experience

5+ years of professional software engineering experience

Strong experience with C# / .NET and Microsoft Azure

Experience building production APIs and backend services

Hands-on experience integrating Generative AI and Large Language Models into production applications

Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines

Experience building agent workflows and intelligent workflow applications

Experience with prompt engineering

Experience with function calling and AI tool orchestration

Experience working with SQL, enterprise systems, and cloud-native architectures

Experience building AI assistants, copilots, or similar intelligent applications

Ability to take AI prototypes and turn them into reliable, production-grade applications

Experience working within financial services or another regulated industry

Desired Skills & Experience

Experience with .NET 8+, ASP.NET Core, and modern C# development

Experience with Azure OpenAI and Azure AI Search

Experience with Azure Kubernetes Service (AKS)

Experience with Azure Functions and Service Bus

Experience with Cosmos DB and SQL

Experience with Docker and containerized applications

Experience with GitHub Actions or Azure DevOps

Familiarity with Semantic Kernel, LangChain, Copilot Studio, Azure AI Foundry, or similar AI orchestration frameworks

Experience with React, TypeScript, Blazor, or Python

Experience developing secure AI applications in enterprise environments

Strong understanding of cloud-native application architectures

What You Will Be Doing Daily Responsibilities

Build AI-powered applications using C#, .NET, and Azure

Design and implement RAG pipelines that connect LLMs with enterprise data and systems

Develop agentic workflows that enable AI applications to reason, interact with tools, and execute business processes

Integrate LLMs into production applications using APIs, function calling, and tool orchestration

Develop backend services and APIs that expose AI capabilities to internal applications and workflows

Implement guardrails, validation logic, observability, and human-in-the-loop workflows

Build AI assistants, copilots, and intelligent workflow applications for financial services use cases

Integrate AI capabilities with enterprise systems, databases, and cloud-native services

Work closely with Product, Data, Platform, and AI teams to define and deliver production solutions

Evaluate AI prototypes and determine how they can be transformed into secure, scalable production applications

Help establish engineering patterns and best practices for integrating AI into enterprise systems

The Offer

You Will Receive The Following Benefits

Competitive Salary

Hybrid Work Environment

Opportunity to work at the intersection of AI, financial technology, and enterprise software

Hands-on ownership of production AI applications and intelligent workflows

Opportunity to work with modern Azure AI and LLM technologies

Collaborative environment working closely with Product, Data, Platform, and AI teams

Applicants must be authorized to work in the US on a full-time basis now and in the future.

Posted By: James Carmichael