We are seeking a hands-on AI Engineer to design, build, and operate internal AI-powered solutions that significantly improve productivity across IFS.
This is an end-to-end engineering role responsible for delivering user-facing AI applications, backend AI services, enterprise copilots, and workflow automation. The role combines frontend development, AI engineering, and cloud platform integration, primarily within the Microsoft ecosystem, while remaining open to other modern development platforms and cloud technologies when appropriate.
You will work closely with stakeholders to translate business needs into secure, scalable, and maintainable AI solutions aligned with enterprise architecture, governance, and security standards.
This is not a data science role. It is an engineering role focused on building production-grade AI-powered applications.
Key Responsibilities
1. AI Solution Engineering
Translate business requirements into AI-driven technical designs and implementation plans.
Design and implement applications that leverage large language models, embeddings, and retrieval-augmented generation.
Engineer prompt strategies, grounding mechanisms, safety controls, and evaluation methods.
Integrate AI capabilities into enterprise systems and workflows.
2. Frontend Development
Design and develop modern, responsive frontend applications using React and TypeScript.
Build internal AI portals, chat interfaces, dashboards, admin panels, and configuration screens.
Implement advanced AI UX patterns including streaming responses, citations, feedback capture, and role-based controls.
Integrate frontends securely with backend APIs and enterprise authentication mechanisms.
Ensure accessibility, performance, usability, and maintainability standards.
3. Backend & AI Services
Develop backend services and APIs using Azure services or other appropriate cloud platforms.
Integrate with Azure OpenAI, Azure AI Search including vector search, or equivalent AI services.
Design secure RESTful APIs exposing AI capabilities to internal consumers.
Implement authentication and authorization standards such as OAuth2, OIDC, and managed identities.
Ensure monitoring, telemetry, logging, and operational readiness.
4. Copilot & Microsoft Ecosystem Integration
Design and build enterprise copilots using Copilot Studio.
Integrate copilots with Microsoft 365 services such as Teams and SharePoint.
Configure connectors, plugins, and grounding strategies aligned with governance requirements.
Manage lifecycle, security, and compliance considerations for copilot solutions.
5. Automation & Productivity Enablement
Build workflow automations using Power Automate, Azure Logic Apps, Power Platform, or equivalent tools.
Design AI-driven process automation for internal productivity use cases.
Integrate AI solutions into enterprise systems through APIs and orchestration layers.
6. DevOps, Governance & Continuous Improvement
Implement CI/CD pipelines using Azure DevOps, GitHub Actions, or equivalent tooling.
Containerize applications using Docker when appropriate.
Apply GenAI operational practices including prompt versioning, evaluation, monitoring, and incident management.
Maintain architecture documentation, design records, and operational procedures.
Ensure compliance with IT security standards and architectural frameworks.