About the Role
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™.
Responsibilities
We are seeking an experienced Software Engineer to embed directly with customers on scheduling optimisation for Manufacturing, our enterprise scheduling and optimization platform (.NET 10/C# backend, Angular frontend) used to solve complex resource planning and scheduling problems at scale.
This is a hands-on technical role that combines software engineering, applied optimization and direct customer engagement. You will sit at the intersection of our optimization engine and our customers: modeling real-world planning problems, and shipping working solutions fast, embedded with customer teams under tight deadlines. This role suits an engineer who wants to solve hard optimization problems in the field, work directly with customers, and feed what they learn back into the core product. We're AI-first: you'll be expected to make full use of AI-assisted and agentic workflows day to day, and we're looking for someone genuinely enthusiastic about using them to model problems and ship solutions faster.
•Partner directly with customers to translate real-world scheduling and planning problems into optimization models.
•Configure, extend, and debug the core scheduling engine and related components against live customer datasets.
•Build and iterate on new solutions with customer teams, often under tight deadlines.
•Feed field learnings back to core product and engineering teams to improve the platform.
Success in the role looks like:
•Customer scheduling and planning problems modeled accurately and solved within performance targets.
•Working solutions shipped to customers, on tight timelines.
•Optimizer performance and quality issues diagnosed and resolved efficiently.
•Field learnings translated into concrete product and engineering improvements.
•Strong, trusted relationships built with customer teams.
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences.
Requirements
•Strong software engineering background, ideally C#/.NET; comfortable reading and modifying a large codebase.
•Hands-on experience with optimization techniques, constraint programming, mathematical/linear programming, or algorithm development.
•Comfortable working directly with customers: gathering requirements, explaining trade-offs, and presenting results.
•Bias toward shipping, with a willingness to develop and iterate quickly under ambiguity.
•Strong analytical and problem-solving skills, with the ability to work through ambiguous, real-world constraints.
•Experience with Angular/TypeScript or other modern frontend frameworks.
•Background in workforce or resource scheduling domains.
•Experience with large-scale data modelling.
•Familiarity with enterprise SaaS platforms or vertical-specific optimization products.
Technology Stack (Representative)
•Backend: .NET 10, C#
•Frontend: Angular, TypeScript
•Optimization: Constraint programming, mathematical/linear programming, heuristics, algorithm development.
•Deployment: On-site and embedded customer environments, cloud-hosted platform
•Practices: Git, automated testing, DevOps
