Forward Deployed Engineer (FDE)

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.

As a Forward Deployed Engineer, R&D AI Services, you embed directly with product development teams to understand real business problems and work out the right way to solve them with AI: reusing and extending an existing AI service, or — when nothing suitable exists — scoping the requirements and working with the engineering team to build one. You are the bridge between a product team's business flow and a working AI capability: you know the AI service catalogue well enough to match the right service to the problem, you help teams build AI-first applications on top of it, and when a gap exists, you make sure the right thing gets built to close it.

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 data pipeline or model-serving system behind it.

What you'll do

• Embed directly with product teams (your internal customers) to understand their business flows and work out where AI genuinely helps

• Lead technical discovery: separate the actual bottleneck in a business process from the symptom the product team came to you with
• Know the existing catalogue of AI services well enough to spot where one could be applied or extended to solve a product team's problem, and help them design and build AI-first applications on top of it
• Where no existing service fits, gather and document the requirements yourself, then partner with the engineering team responsible for AI services to scope, design, and build the new service — you're hands-on throughout, not just handing off a ticket
• Get hands-on with the data pipelines, model training and serving, and MLOps tooling behind both new and existing AI services, plus the integrations that connect them into product workflows
• Ship a working first version fast, then harden it: proper monitoring, feedback loops from real usage, and production-grade reliability
• Translate product team pain points and business requirements into actionable input for the AI services roadmap
• Work directly with product owners, business stakeholders, and engineering leads — going deep into the data and code while communicating trade-offs clearly to non-technical audiences
• Be the connective tissue between IFS R&D's AI capability and the product teams consuming it — your field insights shape what gets built next

Qualifications

• 5+ years of software engineering experience, with strong hands-on capability building and deploying production systems and the ability to work across an unfamiliar stack when needed.
  • Languages: Strong Python, with the ability and willingness to work across other languages and existing customer codebases.
  • Cloud & Kubernetes: Experience building and operating cloud-native services. Azure experience - particularly AKS, Blob Storage, Key Vault, and Azure-hosted AI/model services - is highly relevant.
  • AI & LLM Integration: Experience integrating LLMs and AI services into production applications, including model APIs, authentication, gateways, reliability, latency, cost, and observability.
  • Agentic Systems: Experience building agentic applications using tools, APIs, and orchestration frameworks. Hands-on MCP experience is strongly preferred.
  • Retrieval & RAG: Hands-on experience designing production RAG and retrieval systems, including embeddings, vector databases, indexing, retrieval quality, and evaluation.
  • APIs & Enterprise Integration: Strong experience with REST APIs, authentication/authorization, external systems, data contracts, and debugging complex integrations.
  • Deployment & IaC: Docker, Kubernetes, Helm, GitOps/ArgoCD, and Terraform or equivalent infrastructure-as-code tooling.
  • Data & Storage: Comfortable working with data pipelines and across relational, document, vector, and object stores as required by the solution.
• Solid understanding of event-driven and distributed systems architecture, applied pragmatically in delivery contexts rather than academically
• Understanding of AI evaluation, observability, monitoring, failure modes, and the trade-offs between quality, latency, reliability, and cost.
• Experience building and owning production ML/data systems (not just notebooks or prototypes), 
• You thrive in ambiguity - you can turn "this business flow feels like it needs AI" into a scoped, shipped system without waiting to be told exactly what to build
• You communicate well with non-technical stakeholders without dumbing down the substance
• Experience working in or alongside platform or infrastructure teams
• Able to work directly with customers and stakeholders, turn ambiguous business problems into technical solutions, rapidly prototype, and then productionize those solutions.

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.

In Industrial and Financial Systems Central and Eastern Europe Sp. z o.o., based in Warsaw, the Whistleblowing Procedure is in effect, outlining the methods for reporting legal violations, rules for accepting internal reports and taking follow-up actions, as well as the principles for protecting whistleblowers. Reports can be submitted through the application at https://report.whistleb.com/pl/ifs, available on the website https://www.ifs.com/.