What youll 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 reliable, 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
• Positive 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.

📌 Software Engineer (Hyderabad)
🏢 hackajob
📍 Hyderabad