IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.
At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust.
We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.
By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.
We’re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.
If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS.
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.
Technical Skills
AI & LLM Engineering
- Strong understanding of large language models, embeddings, vector search, and retrieval-augmented generation.
- Practical experience integrating generative AI APIs into enterprise applications.
- Experience implementing prompt engineering, grounding techniques, and AI evaluation strategies.
- Familiarity with vector-capable databases or search platforms.
Frontend Development
- Strong experience with React and TypeScript in production environments.
- Experience with modern frontend tooling such as Next.js or similar frameworks.
- Solid understanding of component architecture, state management, API integration, and UI performance.
- Experience implementing secure authentication flows in frontend applications.
Backend & Cloud Engineering
- Proficiency in Python, C#/.NET, or TypeScript/Node.js.
- Experience designing and building secure REST APIs and microservices.
- Strong knowledge of cloud-native architectures and service-oriented design.
- Experience with Azure cloud services is highly desirable.
- Experience with other cloud platforms or development ecosystems such as AWS, GCP, or other modern frameworks is also valued.
Microsoft Ecosystem & Automation
- Hands-on experience with Copilot Studio.
- Experience with Power Platform, Power Automate, Azure Logic Apps, or similar automation tools.
- Familiarity with Microsoft 365 integrations such as Teams and SharePoint.
- Strong scripting and automation skills using PowerShell, Bash, or JavaScript.
DevOps & Operational Practices
- Experience with CI/CD pipelines.
- Familiarity with containerization technologies such as Docker.
- Understanding of monitoring, logging, and observability best practices.
- Strong documentation discipline and engineering rigor.
Experience Requirements
- 3 to 5 years of professional software engineering experience.
- At least 1 to 2 years delivering generative AI solutions in a cloud environment.
- Proven experience building frontend applications for enterprise or internal platforms.
- Experience integrating LLM capabilities into production systems.
- Demonstrated ability to design secure, scalable, and maintainable applications.
- Experience working in cross-functional, distributed teams.
Education
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience.
Preferred Certifications
- Microsoft Certified: Azure AI Engineer Associate (AI-102)
- Microsoft Certified: Azure Developer Associate (AZ-204)
- Microsoft Certified: Power Platform Developer Associate (PL-400)
- ITIL Foundation
