Full Stack AI Developer

Our partner is a U.S.-based international bank expanding how artificial intelligence supports secure, regulated financial operations. As part of this initiative, they are adding an AI Developer to build backend AI solutions that automate workflows and connect intelligent agents with existing enterprise systems. You’ll work primarily in Python, developing AI agents, RAG-based solutions, and workflow integrations that interact with APIs, databases, and business platforms. This is software engineering first, with AI applied to real operational problems rather than experimental research.

The environment is highly regulated, so successful solutions must balance functionality with security, governance, reliability, and compliance. It’s a strong fit for an engineer who enjoys figuring things out, building practical systems, and growing deeper into production AI development.

Experience and Education:

• BS in Computer Science, Information Technology, Software Engineering, or equivalent experience/field
• Strong software engineering background with hands-on Python development
• Proven work building or supporting backend applications, services, or workflow-driven systems
• Hands-on exposure to AI agents, LLM applications, or production AI solutions
• Familiarity integrating applications with APIs, databases, and enterprise systems
• Background working within regulated, compliance-driven, or data-sensitive environments
• Exposure to cloud-based application development

Skills and Strengths:

• Python
• AI Agent Development
• Retrieval Augmented Generation
• API Integration
• Workflow Automation
• Database Integration
• Software Architecture
• Tool Calling
• Agent Orchestration
• Prompt Engineering
• REST APIs
• Application Security
• AI Governance
• Regulatory Compliance

Primary Job Responsibilities:

• Develop backend AI applications and workflow-driven solutions using Python
• Build AI agents that support and automate internal business processes
• Implement Retrieval-Augmented Generation solutions for enterprise use cases
• Connect AI applications with APIs, databases, and existing business systems
• Develop agent workflows capable of retrieving information, applying business logic, and completing defined tasks
• Integrate AI capabilities into existing enterprise and banking workflows
• Evaluate AI tools and technical approaches based on business requirements
• Apply software engineering practices to AI development, testing, deployment, and maintenance
• Build safeguards and controls appropriate for a regulated environment
• Support secure handling of sensitive business and customer data
• Troubleshoot integration, workflow, and application reliability issues
• Collaborate with business, technology, risk, and compliance stakeholders
• Contribute to technical decisions involving performance, complexity, cost, and maintainability
• Learn and adapt to new AI technologies as the organization’s capabilities evolve
• Help move AI concepts from experimentation into practical production use