Principal Software Engineer
Job description
About the role
This role delivers scalable Generative AI solutions across the full stack, connecting user interfaces, APIs, and agentic workflows for enterprise customers. It leads end-to-end design, implementation, and reliability of intelligent planning experiences. Success is measured by robust, automated planning outcomes for global customers.
Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.
Key facts
What you'll do
Production systems translate business needs into scalable Generative AI solutions that serve frontend and backend services.
Backend API services, custom tools, LLM integrations, and evaluation frameworks are built to support comprehensive GenAI features.
Orchestration, tool-calling, and multi-agent coordination are implemented to enable reliable AI workflows.
Full-stack capabilities are driven through responsive React and TypeScript frontends alongside Python, Java, Kotlin, or Node.js backend services.
Platform reliability is championed through high availability, performance optimization, and reduced MTTD and MTTR across services.
Requirements
The posting states a bachelor's degree requirement. Extensive professional software engineering experience is required with a record of delivering complex, high-quality technical projects in senior or principal roles.
Deep hands-on experience designing, deploying, and scaling agentic AI workflows, tool integrations, and GenAI features is necessary in production environments.
High proficiency in modern frontend frameworks, specifically React and TypeScript, and robust backend development in Python, Java/Kotlin, or Node.js is mandatory.
Deep understanding of LLM APIs, prompt engineering, agentic/multi-agent architectures, and building or consuming Model Context Protocol services is essential.
Strong experience with application observability, logging, and performance monitoring across distributed backend systems and frontend applications is required.
Exceptional communication skills enable effective collaboration across engineering, product, and design teams from prototype to production.
Practical notes
This role is based in Manchester, United Kingdom.
The interview process involves multiple stakeholders and no offers are extended without formal interviews.
C andidate data is processed in line with Candidate Privacy Notice, including possible use of automated evaluation tools.
Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
The role emphasizes diversity, equity, inclusion, and belonging as core drivers of innovation and market leadership.
Technical work spans modern web frameworks, cloud-native microservices, and enterprise AI toolchains.
Engineers work across frontend and backend stacks to deliver reliable, observable AI-powered planning experiences.
The culture values ownership, continuous learning, and celebrating wins at all levels.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.