Lead / Senior Software Engineer

IFS; Greater London; On-site; GBP 90,000 - 135,000; Full time

Job summary

IFS is seeking a Lead/Senior Software Engineer to join the Enterprise Asset Management team to design, build and evolve modern enterprise software in the cloud.

You will deliver scalable, secure systems, guide architecture, and apply AI capabilities where they create value. You’ll work on domain-driven, microservices-based solutions using Go, TS/Node, Kubernetes, and cloud services.

This role requires real customer-facing impact and leadership in production-grade software.

Qualifications

• Degree in Computer Science/Software Engineering/Information Technology with at least 6 years’ experience.
• Strong hands-on experience with Go and TypeScript/Node.js.
• Experience designing distributed systems, microservices and cloud-native apps.

Responsibilities

• Design, build and evolve scalable, secure enterprise software.
• Lead development of distributed systems, microservices and APIs.
• Integrate AI capabilities into production software and leverage LLMs.

Skills

Go

Node.js/TypeScript

Distributed systems

Microservices

REST APIs

DDD

Event-driven

Service decomposition

Kubernetes

Kafka

PostgreSQL

MongoDB

AWS

Azure

CI/CD

Observability

DevSecOps

LLMs

AI integration

Education

Degree in Computer Science/Software Engineering/Information Technology

Job description

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.

Technical Skills Required:

• Strong hands-on experience with Go and modern backend development, ideally alongside TypeScript/Node.js.
• Experience designing and building distributed systems, microservices and RESTful APIs.
• Strong understanding of Domain-Driven Design (DDD), bounded contexts, event-driven architecture and service decomposition.
• Experience building scalable cloud-native applications using technologies such as Kubernetes, Kafka, Redpanda, PostgreSQL and MongoDB.
• Experience working with AWS and/or Azure.
• Strong understanding of CI/CD, automated testing, observability and production operations.
• Experience designing secure software, authentication and authorisation mechanisms and applying DevSecOps principles.
• Experience integrating AI capabilities into production software to solve real customer or business problems.
• Hands-on experience working with Large Language Models (LLMs) within enterprise applications.
• Understanding of modern AI application patterns such as Retrieval-Augmented Generation (RAG), tool calling, prompt engineering and agentic workflows.

Qualifications:

• A degree in Computer Science, Software Engineering or Information Technology along with minimum 6 years' experience in a similar role.
• Excellent communication and multi-tasking skills along with an innovative mindset. Degree in Computer Science, Software Engineering or Information Technology, Minimum 6 years' experience in a similar role, Strong hands-on experience with Go, Experience with TypeScript/Node.js, Experience designing distributed systems and microservices, Understanding of Domain-Driven Design (DDD), Experience with Kubernetes, Kafka, Redpanda, PostgreSQL and MongoDB, Experience with AWS and/or Azure, Experience integrating AI capabilities and LLMs into production software, Understanding of RAG, tool calling, and agentic workflows