We are looking for a talented Lead/Senior Software Engineer to join our Enterprise Asset Management team and play a leading role in designing, building and evolving modern enterprise software.
You'll help deliver scalable, secure and high-quality software that solves complex customer challenges while applying modern engineering practices and AI capabilities where they create genuine business value.
We're looking for experienced Lead/Senior Software Engineers who have built and shipped complex production systems and who understand how emerging AI technologies can be successfully integrated into enterprise products. This is not an AI research or AI platform engineering role. Instead, you'll work on real customer problems, building domain-driven software where AI enhances product capabilities and customer outcomes.
The ideal candidate will demonstrate strong technical leadership, excellent problem-solving and communication skills, and a proven track record of delivering high-quality enterprise software at scale. You'll work closely with Product, Design and Engineering teams to build intelligent Enterprise Asset Management solutions, mentor engineers, drive engineering excellence and help shape the future of enterprise software at IFS.
Engineering Mindset
You are first and foremost a software engineer who enjoys solving complex business problems through well-designed software.
You understand how to design scalable systems, model complex business domains and build software that is reliable, maintainable and easy to evolve.
You recognise AI as an important capability within modern software engineering and understand how technologies such as Large Language Models (LLMs) can enhance enterprise applications when applied to genuine customer problems.
You balance innovation with simplicity, maintainability, security and operational excellence, making pragmatic engineering decisions that deliver long-term value.
Above all, you care about building great software that customers rely on every day.
Business Mindset
Aligns engineering decisions with business goals, focusing on initiatives that deliver measurable customer value.
Understands the commercial impact of technical decisions and identifies opportunities where AI and modern technologies can improve business processes, user experiences and operational efficiency.
Balances innovation with practicality, helping teams make decisions that support long-term product success.
Builds for Customers
Demonstrates a customer-first mindset by making technical decisions based on customer needs and business outcomes.
Works closely with Product Management and stakeholders to understand operational challenges and designs software that simplifies workflows, improves decision-making and delivers measurable value.
Applies AI capabilities thoughtfully where they genuinely improve customer experiences rather than adopting technology for its own sake.
Drives Progress with Accountability
Takes ownership of delivering high-quality software by removing blockers, maintaining engineering standards and supporting teammates.
Delivers on commitments while communicating risks early and making pragmatic decisions around technical debt, architecture, quality and delivery.
Champions continuous improvement across engineering practices, software quality and team collaboration.
Technical Skills
Required
Software Engineering
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Strong hands-on experience with Go and modern backend development, ideally alongside TypeScript/Node.js.
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Experience designing and building distributed systems, microservices and RESTful APIs.
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Strong understanding of Domain-Driven Design (DDD), bounded contexts, event-driven architecture and service decomposition.
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Experience building scalable cloud-native applications using technologies such as Kubernetes, Kafka, Redpanda, PostgreSQL and MongoDB.
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Experience working with AWS and/or Azure.
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Strong understanding of CI/CD, automated testing, observability and production operations.
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Experience designing secure software, authentication and authorisation mechanisms and applying DevSecOps principles.
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Strong analytical and problem-solving skills with the ability to mentor engineers and lead technical initiatives.
Applying AI in Enterprise Software
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Experience integrating AI capabilities into production software to solve real customer or business problems.
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Hands-on experience working with Large Language Models (LLMs) within enterprise applications.
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Understanding of modern AI application patterns such as Retrieval-Augmented Generation (RAG), tool calling, prompt engineering and agentic workflows where appropriate.
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Experience evaluating AI-enabled features for quality, reliability, performance, security and operational readiness.
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Experience using AI-assisted engineering tools such as GitHub Copilot, Cursor or Claude Code to improve software development workflows.
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Appreciation of responsible AI practices including governance, monitoring and observability.
Beneficial
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Experience with React and modern frontend development.
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Experience building Enterprise SaaS or ERP products.
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Experience working with Model Context Protocol (MCP) or similar AI integration standards.
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Experience with vector databases, AI observability or AI evaluation frameworks.
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Experience designing and delivering enterprise-scale AI platforms or AI-powered products.
