About the Company

Dar Al-Handasah (Shair and Partners) is a renowned multidisciplinary consultancy firm specializing in Architecture, Engineering, Planning, and Environmental Design. With a legacy of over 60 years, we have a global presence and a commitment to delivering innovative and sustainable solutions to our clients' most complex challenges. Our diverse team of professionals collaborates across disciplines to create iconic projects that shape cities and improve lives.

About the Role

Backend Lead Developer

Role Summary The Backend Lead Developer owns the technical health and delivery of the backend team. They combine hands-on engineering leadership — code quality, architecture, deployments, and mentoring — with active, daily use of AI tools to accelerate delivery without compromising engineering rigor. This role sets the standard for how the team builds software, including how it uses AI responsibly and effectively.

Key Responsibilities

Code Review & Quality Assurance Review all merge requests for clarity, performance, and maintainability. Validate architectural compliance and flag inconsistencies or risks to keep the codebase stable and high quality across all services.

Planning, Estimation & Sprint Participation Participate in sprint planning, refinement, and backlog alignment. Provide accurate effort estimates and story points based on complexity and scope, keeping priorities clear and achievable.

Ticket Management & Delivery Oversight Oversee all tickets through the development cycle — ensuring each is properly handled, unblocked, and completed on time. Track progress, follow up regularly, and resolve technical or functional uncertainties.

Team Coordination & Follow-Up Maintain regular communication with developers to monitor progress, clarify requirements, and surface obstacles early. Balance task allocation so no one is overloaded or underutilized.

Deployments & Release Management Supervise deployments across development, staging, and production. Coordinate with infrastructure and QA to ensure smooth rollouts, complete pre-release checks, and fast recovery plans.

Documentation & Technical Writing Ensure APIs, workflows, architecture decisions, and system behaviors are clearly documented, reducing onboarding effort and knowledge gaps.





Mentoring & Team Development Provide hands-on guidance to developers at all experience levels, coaching them through problem-solving and architectural decisions to raise the team's overall technical capability.

Problem Resolution & Operational Support Step in during resource shortages, workload spikes, or urgent production issues, coordinating quick solutions to keep operations moving.

High Availability & Platform Reliability Monitor performance indicators, identify bottlenecks, and proactively address risks to keep the backend platform reliable, responsive, and highly available.

Cross-Functional Collaboration Communicate regularly with PMs, POs, QA, and frontend teams to align expectations, share timelines, and remove dependencies.

Final Review Before Release Perform a final review of merge requests before they reach release or production branches, confirming stability and consistency and screening out regressions or performance risks.

AI Skills & Modern Development Practices

AI is an integral, daily part of our software development process. As Lead Developer, this role also sets the standard for how the team uses AI responsibly and effectively.

Required AI Skills & Expected Proficiency

- Advanced proficiency directing AI coding assistants to generate, refactor, and debug production-grade code — this is a required, daily-use skill for this role (a higher bar than for individual-contributor developers, since the Lead also reviews others' AI-assisted work).
- Working understanding of how LLMs behave: context limitations, hallucination risk, and the judgment to know when not to trust AI output.
- Ability to critically review AI-generated code to the same bar as human-written code — correctness, security, performance, and architectural fit.
- Skill in task decomposition and context/prompt engineering — breaking complex problems into steps an AI tool can act on effectively.




- Awareness of data privacy and IP considerations when using AI tools against proprietary code, and ability to apply and enforce the organization's AI usage policy across the team.

Experience with AI Coding Assistants & Modern AI Development Tools

- Hands-on, daily experience with at least one major AI coding assistant (e.g., GitHub Copilot, Cursor, Claude Code or equivalent).
- Practical experience using AI across the full development lifecycle: design/architecture exploration, code generation, debugging, test generation, documentation, and code review.
- Familiarity with AI-assisted technical research (evaluating libraries, frameworks, or approaches).
- Experience embedding AI tools into team workflows — e.g., PR review assistance, CI/CD checks, or onboarding documentation.

Practical AI Experience Candidates Must Demonstrate

- Candidates should be able to speak to concrete, specific examples such as: A real feature shipped or production issue resolved with significant AI assistance, including how the output was validated before merge.
- Using AI to generate or strengthen an automated test suite.
- Using AI to produce or maintain technical documentation.
- Walking through an actual prompt/session showing how they iterated with an AI tool to reach a working, secure solution.
- A specific instance where AI-generated code or output was wrong, how it was caught, and how it was corrected — demonstrating judgment, not just tool usage.

Requirements & Qualifications

- 10+ years of backend development experience, including 2+ years in a technical leadership or team lead capacity.
- Proven experience with [core backend stack — e.g., languages, frameworks, databases, cloud provider].
- Experience with CI/CD pipelines and managing deployments across development, staging, and production environments.
- Strong written and verbal communication skills; comfortable working cross-functionally with PMs, QA, and frontend teams.
- Demonstrated mentoring or team-leadership experience.

Qualification:

- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Meets the AI skills, tool experience, and practical AI experience requirements outlined above.

📌 Backend Lead Developer (Bengaluru)
🏢 Dar
📍 Bengaluru