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.

Candidates whose AI experience is limited to using tools such as ChatGPT, Claude, Cursor or GitHub Copilot to assist software development, without demonstrable experience building AI-powered products or systems, will not meet the requirements for this role.

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.

Most engineers ship into a backlog. You'd ship into a customer's operation.

We build the workforce, project, scheduling and service systems companies use to run the physical world — manufacturing, energy, aerospace and defense, construction, telecom, field service. As a Forward Deployed Engineer you embed directly with those customers, work out where software and AI genuinely help, and build it in front of them. Days and weeks, not quarters.

This is a high-agency role for a hands-on senior engineer who is as comfortable in a stakeholder conversation about a business process as they are building and shipping the service behind it.

What you'll do

• Embed with customers to understand their actual operation — their data, their constraints, their people — rather than working from a requirements document written by someone who's never been on site
• Lead technical discovery: separate the real bottleneck from the symptom the customer came to you with
• Design and ship full-lifecycle features across front-end and back-end, and build or extend the APIs and event-driven services that connect workforce, project, scheduling and financial data across IFS Cloud and customer systems
• Know the platform and AI service catalogue well enough to spot what can be reused or extended, and help customers build on top of it
• Where nothing fits, gather the requirements yourself and partner with the owning engineering team to scope and build it — hands-on throughout, not handing off a ticket
• Get into the data pipelines, model serving, retrieval and evaluation behind AI-backed features, and the integrations that put them into a real workflow
• Ship a working first version fast, then harden it: monitoring, feedback loops from real usage, production-grade reliability
• Decide what survives. Some of what you build proves a point and gets deleted; some becomes product for every customer. Calling that correctly, and telling a customer no, is part of the job
• Communicate trade-offs clearly to product owners, customer architects and non-technical stakeholders, and turn what you learn in the field into input for the roadmap

Why you'd want this

• You see the consequences. 
• A new problem every few months. 
• AI-native, for real. 
• Full ownership. 
• A real path back into product. 

• Attitude

  Speed and attitude first. You thrive in ambiguity — you can turn "this process feels like it needs AI" into a scoped, shipped system without waiting to be told exactly what to build. Blocked, you find the way through, escalate early, or change the approach. You don't wait.

  Customers trust you quickly because you're straight with them. You can talk to an architect and a shop-floor supervisor on the same day and be useful to both, without dumbing down the substance.

  The bar

• 5+ years building and operating production systems, with the ability to work across an unfamiliar stack or customer codebase
• Languages: strong in at least one modern general-purpose language, Python included or picked up fast
• Cloud and Kubernetes: building and operating cloud-native services. Azure — AKS, Blob Storage, Key Vault, Azure-hosted AI services — is highly relevant
• AI and LLM integration: LLMs in production applications — model APIs, auth, gateways, reliability, latency, cost, observability
• Agentic systems: agentic applications using tools, APIs and orchestration frameworks. Hands-on MCP strongly preferred
• Retrieval and RAG: production retrieval systems — embeddings, vector stores, indexing, retrieval quality, evaluation
• APIs and enterprise integration: REST, auth/authz, data contracts, and the patience to debug someone else's system
• Deployment and IaC: Docker, Kubernetes, Helm, GitOps/ArgoCD, Terraform or equivalent
• Data: pipelines and comfort across relational, document, vector and object stores
• Pragmatic grasp of event-driven and distributed systems, and of AI failure modes and the quality/latency/reliability/cost trade-offs
• Genuinely fluent with agentic tooling in daily engineering work, not just aware of it 

Desireable

• Enterprise or ERP software. Project- or asset-heavy industries. Consulting or solution engineering. Experience working alongside platform or infrastructure teams. Agile delivery with globally distributed teams.

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.