About the role
The Software Engineer Professional is a handson software engineer who delivers highquality software as part of a small, outcomefocused pod of typically 45 engineers. The role operates in an AInative delivery model, where AI tools and agents are used across the software development lifecycle (SDLC) to accelerate delivery, improve quality, and reduce manual effort. Unlike traditional engineering roles, the Pod Engineer is expected to work with AI as a core delivery partner, using AI tools for requirements understanding, design exploration, code generation, testing, documentation, and optimisationwhile remaining accountable for correctness, security, and production readiness. What youll need to succeed (Skills & Experience) Essential
- Strong experience as a software engineer delivering production systems.
- Solid foundations in software engineering fundamentals: data structures, APIs, testing, CI/CD, and debugging.
- Proven expertise in Java, Python along with UI and backend technologies like React, PostgreSQL, Neptune DB.
- Strong credentials in Cloud environments like AWS.
- Experience working in Agile / iterative delivery environments.
- Practical exposure to AIassisted development tools (e.g. Copilot, Amazon Kiro, Claude Code, automated testing, AIsupported documentation).
- Possess B. Tech or B.
E. degree in Computer Science or related field. Desirable
- Experience working in small squads or pods with shared ownership of outcomes.
- Familiarity with cloud platforms and modern delivery pipelines.
- Curiosity and enthusiasm for using AI to improve how software is built. What you will be doing (Role Accountabilities) 1) HandsOn Software Delivery
- Design, build, test, and deploy software components as part of a delivery pod.
- Contribute productionquality code across backend, frontend, APIs, or integration layers, depending on the pods scope.
- Own features endtoend—from understanding requirements through to deployment and support. 2)



AIEnabled SDLC Execution
- Use AI tools and assistants across delivery stages to:
- accelerate understanding of requirements and acceptance criteria
- generate and refine code safely
- create and maintain automated tests
- support documentation and release artefacts
- Apply judgment to validate AIgenerated outputs, ensuring correctness, maintainability, and security.
- Continuously improve personal and podlevel productivity through effective AI usage. 3) Engineering Quality & Standards
- Write clean, maintainable, welltested code aligned to agreed engineering standards.
- Participate actively in code reviews, pair programming, and design discussions.
- Follow secure coding practices and ensure solutions meet performance, reliability, and resilience expectations. 4) Pod Collaboration
- Work closely with the Pod Lead Engineer and other Pod Engineers to deliver outcomes as a cohesive unit.
- Contribute to daily planning, reviews, and retrospectives.
- Support knowledge sharing, experimentation, and continuous improvement within the pod. 5) Learning & Capability Development
- Continuously develop skills in modern software engineering and AIassisted development techniques.
- Adopt and share good practices for prompt design, AI evaluation, and protected AI usage.
- Stay current with emerging tools, frameworks, and patterns relevant to AIenabled engineering. 6) Governance, Risk & Responsible Engineering
- Adhere to security, data protection, and governance requirements.
- Flag risks, defects, or concerns early—especially those introduced by AIassisted development.
- Ensure delivery artefacts are complete, auditable, and fit for production use. What Makes This Role Different from a Traditional Software Engineer
- You work in small, highimpact pods, not large project teams.
- AI is used by default across the SDLC, not occasionally.
- Success is measured by outcomes, quality, and speed, not just code output. You are expected to think critically about AI outputs, not blindly accept them.

📌 Walk-in || Java Full Stack Developer (Bengaluru)
🏢 BT Group
📍 Bengaluru