Lead / Senior Software Engineer || Enterprise Asset Management AI & Agentic Systems

About the role

IFS is a global enterprise software company that builds solutions for managing physical assets across industries worldwide. The Lead / Senior Software Engineer for Enterprise Asset Management AI and Agentic Systems will work on intelligent software platforms that help organizations track, maintain, and optimize their physical assets using artificial intelligence and autonomous agent technologies. This role is part of a dedicated team at IFS that is building next-generation AI systems within the enterprise asset management domain. You will contribute to designing and implementing software that brings automated reasoning and intelligent decision-making to asset-intensive operations in sectors such as manufacturing, energy, and public infrastructure. The team works within IFS's enterprise asset management product portfolio, contributing to platforms that serve customers managing billions of dollars in physical infrastructure and equipment.

Key facts

What you'll do

• Design and build AI-powered features for enterprise asset management platforms at IFS
• Develop agentic systems that can autonomously reason about asset maintenance and operations
• Work on the full software lifecycle from prototyping through production deployment
• Collaborate with cross-functional teams including product, data science, and domain specialists
• Write clean, maintainable, and well-tested code for distributed systems serving enterprise customers
• Participate in code reviews and contribute to architectural decisions for AI systems
• Research and evaluate new approaches to applying AI in asset management contexts
• Build and maintain APIs and data pipelines that support intelligent asset workflows
• Mentor junior engineers and contribute to the technical growth of the team
• Translate business requirements from asset management domain into clear technical specifications
• Optimize system performance and reliability for AI-driven enterprise applications in production
• Contribute to documentation and knowledge sharing across the engineering organization regularly
• Ensure that AI features meet quality standards, security requirements, and compliance obligations for enterprise customers

Requirements

• Demonstrated experience as a senior or lead software engineer building production-grade systems over multiple years
• Strong understanding of artificial intelligence concepts and their practical application in real-world software products
• Experience working with enterprise-scale software platforms and distributed systems that serve many customers
• Ability to design and implement autonomous agent architectures and workflows for complex business domains
• Familiarity with enterprise asset management domains or related industrial software and operational contexts
• Proficiency in modern programming languages commonly used for building AI-driven applications and services
• Experience collaborating with multidisciplinary teams including data scientists, product managers, and domain experts
• Strong problem-solving skills and the ability to work through ambiguous and evolving technical challenges
• Comfort with taking ownership of architectural decisions and seeing features through from design to production
• Effective communication skills for presenting technical approaches and trade-offs to both technical and non-technical stakeholders
• A commitment to writing thorough documentation, tests, and operational runbooks that support long-term system reliability

Nice to have

• Experience with large language models or generative AI technologies in production settings at scale
• Background in asset-intensive industries such as oil and gas, manufacturing, or utilities and related sectors
• Familiarity with cloud-native deployment patterns, containerized workloads, and infrastructure-as-code approaches
• Contributions to open source projects or published work in artificial intelligence or software engineering

Skills & tools

• Programming languages commonly used for building AI applications and backend services at scale
• Frameworks and libraries for constructing intelligent applications and agentic workflow systems
• Cloud platforms and infrastructure services for deploying enterprise software to global customers
• Database systems and data storage solutions for handling large volumes of enterprise asset data
• API design and integration patterns for connecting AI services with business-facing applications
• Version control systems and collaborative development workflows used in modern engineering teams
• Monitoring, logging, and observability tools for maintaining reliable software in production environments

Practical notes

• This role is based in London and requires regular on-site presence at the IFS office
• The position is full-time with standard business hours and occasional flexibility for focused deep-work sessions
• Candidates should be prepared to work within the IFS engineering culture, established processes, and collaborative norms
• The hiring process includes technical interviews, system design discussions, and a thorough review of relevant experience
• This is a permanent full-time position with opportunities for professional development and career advancement at IFS
• IFS offers a collaborative engineering environment with access to modern development tools and continuous learning resources