At IFS, we're building the next generation of AI-native enterprise software, transforming how some of the world's largest organisations manage assets, operations and critical services.
This is an opportunity to work at the forefront of modern AI engineering, building intelligent products that combine Large Language Models (LLMs), agentic AI and cloud-native technologies to solve complex, real-world business challenges at enterprise scale.
We're looking for engineers who are passionate about building production AI systems and excited by the opportunity to shape the future of enterprise software.
Please note that this role requires demonstrable, hands-on experience designing, building and shipping production AI applications.
IFS is a billion-dollar revenue company with 7000+ employees on all continents. We deliver award-winning enterprise software solutions through the use of embedded digital innovation and a single cloud-based platform to help businesses be their best when it really matters–at the Moment of Service™.
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 accept that there are so many different perspectives in this world. 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.
If you want to change the status quo, we'll help you make your moment. Join Team Purple. Join IFS.
Job DescriptionBuild and operate the interface, semantic layer and controls that let AI agents work inside IFS software safely.
Key responsibilities
Design and build MCP servers (Model Context Protocol, the emerging standard for exposing application capability to agents) over the product’s business objects, treating capability modelling, discoverability, versioning and backward compatibility as first-class design problems.
Build the write path that lets an agent safely change a customer’s operational data.
Build the semantic layer: an ontology and knowledge graph over the product, generated from what the platform already knows about itself and then curated industry by industry.
Build the skills layer that maps what someone asks for onto the correct operation and the correct sequence, with a router that picks between them.
Build the control plane: authentication, entitlements, agent identity, telemetry, metering, resistance to injection, and a default that denies rather than permits.
Build the evaluation harness that certifies agent behaviour against the real product, and improve the system against what it measures.
Build rapid prototypes and proofs of concept to validate emerging technology, product opportunities and customer scenarios.
Establish the engineering practices these systems need: evaluation, testing, observability, monitoring, governance, security and operational excellence.
Contribute to technical design, review other engineers’ work, and support colleagues coming into the domain.
Represent the work outside the team through customer engagements, demonstrations, industry events and partner collaboration.
Qualifications
Strong software engineering first. Everything else is applied on top of that.
Production experience building and operating enterprise systems, with real depth in distributed systems, cloud-native architectures, API and schema design, event-driven systems, security, observability and CI/CD.
Strong programming in a modern backend language. See the note on language under “Open calls” before advertising.
Experience delivering AI systems built on large language models, retrieval-augmented generation (RAG), agentic workflows and orchestration frameworks, including tool use, function calling, workflow orchestration and autonomous or multi-agent architectures, with the judgement to know where they fail.
Evaluation as a discipline: experimentation, benchmarking, prompt engineering, tracing, quality measurement and agent tuning, improving an agent against evidence rather than impression.
Ability to design solutions that integrate enterprise applications, business processes, workflows and data platforms.
Depth in at least one of the following:
Tool-surface and agent-runtime engineering. MCP servers, tool ecosystems, capability modelling, discoverability, governance, versioning, backward compatibility, multi-tenancy isolation.
Knowledge graphs and semantic modelling. Ontology design, context engineering, embeddings, vector databases, retrieval and search technologies, memory architectures, grounding strategies.
Enterprise platform depth. Oracle PL/SQL, OData, and comfort working inside large metadata-driven systems where behaviour is configured rather than coded.
Desirable
Experience with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangGraph, AutoGen, PydanticAI, the OpenAI Agents SDK or CrewAI.
Experience building reusable AI platforms, MCP ecosystems or shared engineering capabilities used across multiple products and teams.
Containerised platforms and infrastructure automation: Docker, Kubernetes.
Experience with Azure, AWS, GCP or another hyperscale cloud platform.
Reverse-engineering or interpreter work.
Token-efficient agent design.
Enterprise software domains: enterprise asset management, service management, manufacturing, supply chain, aerospace and defence, energy, telecommunications, construction, industrial AI.
Contributions to open-source projects, technical communities, conferences, publications or standards.
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.
Skills Required
- Hands-on experience designing, building, and shipping production AI applications
- Production experience building and operating enterprise systems
- Experience with distributed systems and cloud-native architectures
- Experience with API and schema design
- Experience with event-driven systems
- Experience with security, observability, and CI/CD
- Strong programming skills in a modern backend language
- Experience delivering LLM-based AI systems
- Experience with retrieval-augmented generation and agentic workflows
- Experience with orchestration frameworks, tool use, function calling, and autonomous or multi-agent architectures
- Experience with AI evaluation, experimentation, benchmarking, prompt engineering, tracing, quality measurement, and agent tuning
- Ability to integrate enterprise applications, business processes, workflows, and data platforms
- Depth in tool-surface and agent-runtime engineering, knowledge graphs and semantic modeling, or enterprise platform technologies such as Oracle PL/SQL and OData
- Experience with agent frameworks such as Semantic Kernel, Microsoft Agent Framework, LangGraph, AutoGen, PydanticAI, OpenAI Agents SDK, or CrewAI
- Experience building reusable AI platforms, MCP ecosystems, or shared engineering capabilities
- Experience with Docker and Kubernetes
- Experience with Azure, AWS, GCP, or another hyperscale cloud platform
- Reverse-engineering or interpreter experience
- Token-efficient agent design experience
- Experience in enterprise software domains such as asset management, service management, manufacturing, supply chain, aerospace and defense, energy, telecommunications, construction, or industrial AI
- Contributions to open-source projects, technical communities, conferences, publications, or standards
IFS Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about IFS and has not been reviewed or approved by IFS.
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Retirement Support — Retirement support is presented as part of the package in North America through a 401(k) plan and references to pension/defined contribution arrangements in some contexts.
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Healthcare Strength — Healthcare coverage is described as available in some regions, including health, dental, life, and disability insurance offerings.
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Strong & Reliable Incentives — Variable pay elements such as monthly bonuses and profit sharing are described as meaningful in certain roles, with bonuses tied to performance outcomes like reduced downtime.
IFS Insights
What We Do
IFS develops and delivers enterprise software for companies around the world who manufacture and distribute goods, build and maintain assets, and manage service-focused operations. Within our single platform, our industry specific products are innately connected to a single data model and use embedded digital innovation so that our customers can be their best when it really matters to their customers – at the Moment of Service. The industry expertise of our people and of our growing ecosystem, together with a commitment to deliver value at every single step, has made IFS a recognized leader and the most recommended supplier in our sector. Our team of 5,000 employees every day live our values of agility, trustworthiness and collaboration in how we support our 10,000+ customers. Learn more about how our enterprise software solutions can help your business today at ifs.com. Follow us on Twitter: @ifs Facebook: www.facebook.com/ifsdotcom Instagram: www.instagram.com/ifsdotcom Visit the IFS Blog on technology, innovation and creativity: https://blog.ifs.com/









