AI Integration Engineer

Overview

Design, build, and support secure integrations between Digital Coworkers, enterprise applications, APIs, workflows, knowledge repositories, and approved data sources. Focus on enabling AI-powered workflows through scalable integration patterns, RAG architectures, and production-ready solutions.

Key Responsibilities

• Design, develop, test, and support integrations across AI agents, enterprise systems, APIs, and data platforms.
• Build reusable connectors, services, and integration frameworks for Digital Coworker use cases.
• Enable RAG solutions by connecting structured and unstructured data sources.
• Configure tool access, permissions, orchestration workflows, and agent actions.
• Partner with Product, Engineering, Security, Risk, Architecture, and Application teams to ensure secure and compliant implementations.
• Create technical documentation, runbooks, test artifacts, deployment guides, and operational support materials.
• Troubleshoot production issues, perform root cause analysis, and drive long-term remediation.
• Support Agile delivery activities including backlog refinement, sprint planning, release readiness, and dependency management.

Required Qualifications

• 5+ years of experience in Software Engineering, Integration Engineering, Platform Engineering, Cloud Engineering, or similar roles.
• Enterprise-scale integration experience using REST APIs, microservices, event-driven architectures, and service integrations.
• Hands-on cloud development experience, preferably Microsoft Azure.
• Experience supporting production environments, monitoring, incident management, and operational documentation.
• Strong knowledge of security, identity and access management, data protection, logging, and compliance controls.
• Ability to translate business requirements into scalable technical solutions.
• Experience working with Agile tools such as Azure DevOps, Jira, ServiceNow, Confluence, and SharePoint.
• Strong communication, stakeholder management, and documentation skills.

Preferred Qualifications

• Experience in financial services or other highly regulated environments.
• Knowledge of Generative AI, LLMs, AI agents, RAG, prompt engineering, Responsible AI, and AI observability.
• Experience with Azure OpenAI, Azure API Management, Azure Functions, AKS, Microsoft Graph, Copilot Studio, LangChain, LangGraph, and MCP.
• Experience integrating SharePoint, Snowflake, Databricks, Fabric, ServiceNow, and enterprise document repositories.
• Experience creating reusable integration patterns, test plans, release documentation, and support models.

Core Technical Skills

• AI & Agent Platforms: Generative AI, LLMs, AI agents, Digital Coworkers, RAG, prompt engineering, observability.
• Integration Engineering: REST APIs, microservices, event-driven architecture, authentication, error handling, integration testing.
• Cloud & DevOps: Azure, Azure Functions, Azure API Management, AKS, CI/CD, Azure DevOps, monitoring and logging.
• Data & Knowledge Management: SQL, SharePoint, Microsoft Graph, Snowflake, Databricks, Fabric, enterprise knowledge repositories.
• Programming & Tools: Python, LangChain ecosystem, Jira, ServiceNow, Confluence, Power BI, Excel.
• Enterprise Delivery: Governance, security reviews, risk management, operational readiness, production support.