About the role

The Software Engineering Professional supports the execution of BTs software engineering strategy through cross-functional delivery, contributing to the development of technical solutions and platforms that enable innovation and engineering excellence.

What you’ll be doing

1. AI-Driven Product Development (PDLC) 
• AI-driven product development across the full Product Development Lifecycle (PDLC), including 
design, solutioning, development, and unit testing, with an AI-first mindset. 
• Design and deliver high-quality, production-ready solutions, producing clear designs, robust 
solutions, and error-free code with 100%-unit test coverage. 
• Perform wider impact analysis before design and development to ensure new requirements are 
scalable, secure, cost-efficient, and aligned to platform and architectural standards. 
• Work independently with accountability while delivering end-to-end outcomes aligned to colleague 
experience and business priorities. 

2. AI-Enabled ServiceNow Engineering 
• Integrate AI capabilities into the ServiceNow platform to support AI-assisted design, development, 
build, and deployment of colleague experience solutions. 
• Deliver enhancements and new capabilities that improve ServiceNow functionality, usability, and 
automation at scale. 
• Contribute innovation ideas that drive IT transformation, improve platform capabilities, and enhance 
colleague experience. 

3. Production Support & Continuous Improvement 
• Analyse production issues, identify root causes, and deliver timely fixes, improvements, and 
enhancements to ensure service stability and reliability. 
• Continuously identify opportunities to improve product quality, delivery speed, automation, and 
colleague experience outcomes. 
• Ensure solutions remain stable, maintainable, and operationally efficient across their lifecycle. 

4. AI-Assisted Engineering & Automation 
• Leverage AI and automation to streamline development, testing, and deployment processes, reducing 
manual effort and accelerating time to market. 
• Embed AI into engineering ways of working, ensuring consistent and effective use of AI tools across 
development, testing, documentation, and code quality practices. 
• Continuously assess emerging AI engineering tools, frameworks, and patterns, recommending 
adoption where they improve productivity, quality, or cost efficiency. 

5. Governance, Security & Responsible AI 
• Ensure solutions are secure, compliant, and well-governed across development, test, and production 
environments. 
• Set and promote standards for secure and responsible AI usage, including prompt safety, data 
handling, auditability, and risk controls. 
• Contribute to AI governance frameworks and guardrails, supporting lifecycle controls, approvals, and 
risk management without slowing delivery. 
• Collaborate closely with architecture, security, legal, and compliance teams to meet enterprise 
security, privacy, and regulatory requirements. 

6. Leadership, Advocacy & Collaboration 
• Act as an anchor and advocate for AI-driven PDLC, modern engineering practices, and 
automation-led delivery. 
• Provide technical mentoring on AI-assisted engineering, DevOps, and modern development practices. 
• Create and maintain reusable assets, reference implementations, and internal standards to 
accelerate adoption of AI-driven engineering. 
• Act as a trusted engineering partner to product owners, platform teams, operations, and stakeholders 
to shape scalable and sustainable AI use cases.

Essential Skills / Experience

1. AI-Driven Product Development (PDLC) 
• 2+ years’ experience in software engineering using Java, Python, or similar, delivering 
production-ready code. 
• Strong capability across design, solutioning, development, and unit testing, with a focus on quality, 
scalability, and maintainability. 
• Proven experience delivering error-free code with full unit test coverage and performing wider 
impact analysis before implementation. 

2. ServiceNow & AI-Enabled Engineering 
• Hands-on experience developing on ServiceNow (preferred) or similar enterprise platforms. 
• Experience integrating AI capabilities (LLMs, AI agents, RAG patterns) into platforms using APIs and 
event-driven patterns. 
• Exposure to ServiceNow Now Assist, Copilot Studio, KIRO or equivalent AI-enabled tooling is 
desirable. 

3. AI-Assisted Development & Automation 
• Practical experience using AI tools and copilots to accelerate development, testing, documentation, 
and code reviews. 
• Ability to embed AI into engineering workflows to improve productivity and time to market. 
• Strong mindset for automation-first development and deployment 

4. DevOps, Environments & Operability 
• Good understanding of DevOps practices, CI/CD pipelines, and infrastructure as code. 
• Experience working across multi-environment setups (Dev / Test / Prod) with controlled promotion 
paths. 
• Familiarity with containerisation (Docker) and orchestration concepts (Kubernetes – desirable). 
• Ability to analyse and resolve production issues, driving stability and continuous improvement. 

5. Governance, Security & Responsible AI 
• Strong understanding of enterprise security, privacy, and compliance requirements. 
• Experience applying responsible AI practices, including data handling, prompt safety, and auditability. 
• Ability to balance speed of delivery with governance and control. 

6. Professional Capability & Collaboration 
• Ability to work independently with accountability in a fast-paced delivery environment. 
• Strong collaboration skills with product owners, platform teams, and operations. 
• Willingness to share innovation ideas, contribute to reusable assets, and act as an advocate for 
AI-driven PDLC.