At a Glance
- Tasks: Lead the design and development of AI-native enterprise software solutions.
- Company: Join IFS, a billion-dollar tech company transforming enterprise software with AI.
- Benefits: Flexible hybrid work, competitive salary, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace fostering innovation and collaboration.
- Why this job: Be at the forefront of AI engineering and make a real-world impact.
- Qualifications: 6+ years in software engineering with hands-on AI application experience.
The predicted salary is between 63000 - 77000 £ per year.
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.
The ideal candidate will demonstrate strong technical leadership, excellent problem-solving and communication skills, and a proven track record of delivering AI-powered software at scale. In this role, you will design and deliver AI-native Enterprise Asset Management solutions that combine modern cloud technologies with intelligent systems to solve complex business challenges. You'll build scalable, secure and high-quality software while applying AI-assisted engineering practices throughout the software development lifecycle.
As a technical leader, you'll embed AI-first thinking across the team, mentor engineers, drive continuous improvement and help shape the future of enterprise software at IFS.
AI Mindset
You see AI as a fundamental shift in software engineering, not simply another technology or productivity tool. You have experience designing, building and shipping intelligent software using technologies such as Large Language Models (LLMs), agentic AI, orchestration frameworks and intelligent workflows. You're equally comfortable applying AI to solve customer problems as you are using AI-assisted engineering practices to accelerate software delivery.
You naturally consider where AI can create genuine value, balancing innovation with reliability, security, scalability and maintainability. You challenge traditional approaches, embrace experimentation and continuously explore how emerging AI capabilities can improve products, engineering practices and customer outcomes. Above all, you believe the future of enterprise software is AI-native, and you're excited to help build it.
Business Mindset
Aligns engineering decisions with business goals, focusing on initiatives that deliver measurable value. Understands the commercial impact of technical choices and evaluates where AI can create meaningful customer and business outcomes. Balances innovation, investment and technical complexity to help teams make decisions that support long-term organisational success.
Builds for Customers
Demonstrates a customer-first mindset by making technical decisions based on customer needs and feedback. Works directly with customers to understand operational challenges and identify where AI-native capabilities can simplify workflows, improve decision-making and deliver measurable business value. Uses these insights to guide technical direction and prioritise customer outcomes.
Drives Progress with Accountability
Takes ownership of delivering results by removing blockers, setting clear priorities and maintaining high quality standards. Delivers on commitments or raises risks early when plans need to change. Makes pragmatic decisions on technical debt, AI adoption, engineering investments and quality while setting clear expectations and standards for others to follow.
Technical Skills Required
- AI Engineering: Demonstrable experience designing, building and shipping production AI-powered applications.
- Hands-on experience integrating and orchestrating Large Language Models (LLMs) within production software.
- Experience building agentic AI systems, intelligent workflows or AI orchestration capabilities.
- Experience evaluating AI solutions for quality, reliability, latency, cost and security.
- Understanding of prompt engineering, context engineering, Retrieval-Augmented Generation (RAG), tool calling and modern AI application architectures.
- Experience applying AI-assisted engineering practices throughout the software development lifecycle, including specification, implementation, testing and code review.
- Understanding of responsible AI principles, including governance, observability and production monitoring.
- Experience integrating AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code or similar into day-to-day engineering workflows.
Software Engineering
- Strong hands-on experience with Go and modern backend development, ideally with TypeScript/Node.js.
- Experience designing and building microservices, event-driven systems and RESTful APIs using technologies such as Kafka, Redpanda and Kubernetes.
- Solid understanding of Domain-Driven Design (DDD), bounded contexts, service decomposition and distributed system design.
- Experience with PostgreSQL, MongoDB and cloud platforms such as AWS and Azure.
- Strong knowledge of CI/CD, automated testing (unit, integration and end-to-end), observability and production operations.
- Understanding of secure software development, authentication/authorisation and DevSecOps practices.
- Familiarity with AI-assisted Spec-Driven Development (SDD).
- Strong analytical and problem-solving skills, with the ability to lead technical initiatives and mentor engineers.
Beneficial
- Experience with React and modern frontend development.
- Experience building Enterprise SaaS or ERP products.
- Experience working with Model Context Protocol (MCP) or similar AI integration standards.
- Experience with vector databases, AI observability or AI evaluation frameworks.
- Experience designing and delivering enterprise-scale AI platforms or AI-powered products.
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.
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.
Lead Software Engineer | AI & Agentic Systems in London employer: Worky
JPMorgan Chase & Co. is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among talented professionals in the heart of the financial industry. As an Applied AI Engineer, you will have access to extensive employee growth opportunities, cutting-edge technology, and the chance to work alongside industry leaders, all while contributing to impactful projects that shape the future of Markets Operations.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer | AI & Agentic Systems in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Worky or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Worky.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Worky.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Worky that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Lead Software Engineer | AI & Agentic Systems in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Worky.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Worky and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Worky
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Worky uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
