Servicenow Developer - Hardware Asset Management

We are specifically looking for hands-on developers with strong ServiceNow development experience and exposure to Hardware Asset Management (HAM/HAM Pro).

Key skills:

• Strong hands-on ServiceNow development experience
• Hardware Asset Management (HAM)
• Design, development, solutioning, unit testing, and impact analysis
• Experience delivering scalable and production-ready solutions
• Java, Python, JavaScript, or similar programming experience
• Exposure to AI-enabled development, automation, Copilot/Kiro, or DevOps would be an added advantage

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. BT Job Description Confidential 5 of 5 5 of 5 Your name v1.1 Date General • 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.