New opportunity

AVP/VP, Product Engineer (Developer Acceleration), Technology Group

GIC Private Limited · Singapore

About this role

The Product Engineer (Developer Acceleration) will join the Developer Experience team within GIC's Technology Group to build and operate an agentic cloud development platform. This role focuses on enhancing software engineering velocity and quality by integrating AI-native development practices into the software development lifecycle (SDLC). Responsibilities include evolving the agentic cloud development platform, governing developer tools, and driving AI-native adoption across the organization. Key duties involve managing infrastructure, networking, and deployment automation; building processes that connect the platform with enterprise services; and establishing reusable practices for context engineering and agent execution workflows. Candidates must possess 6+ years of experience in software, platform, or infrastructure engineering, with at least 2 years in a technical leadership capacity. Required technical expertise includes proficiency in Python, Java, C#/.NET, or JavaScript/TypeScript; strong AWS skills (EC2, VPC, EKS/ECS, IAM); and experience with IaC (Terraform/CloudFormation), CI/CD, and containerized development. A demonstrated history of using coding agents across the SDLC is essential. The role requires a product-oriented mindset, strong stakeholder management, and the ability to balance developer autonomy with enterprise security and governance requirements. GIC operates on a hybrid model requiring four days per week in the office.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

PythonJavaC#.NETJavaScriptTypeScriptAWSTerraformAWS CloudFormationCI/CDGitOpsDevcontainersInfrastructure as CodeCoding AgentsAgentic SDLCMCP IntegrationsPlatform EngineeringDistributed SystemsKubernetesEKSECS

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Building and Scaling an Agentic Cloud Development Platform
The core mandate is to evolve the platform that supports agentic SDLC workflows. This requires deep technical expertise in AWS infrastructure, containerization (EKS/ECS), and IaC (Terraform) to ensure the platform is resilient, observable, and capable of supporting hundreds of developers.
Driving AI-Native Adoption and Governance
You must establish reusable practices for context engineering and agent execution. This involves balancing the push for developer velocity through AI tools with the necessity of maintaining enterprise-grade security, compliance, and cost control guardrails.
Stakeholder Management and Product Ownership
As a product-oriented engineer, you are responsible for managing a product backlog and aligning the needs of diverse engineering teams with cybersecurity and infrastructure requirements. Success is measured by your ability to translate developer feedback into iterative platform improvements.

Likely challenges to think through

Balancing Developer Autonomy with Strict Security
GIC operates in a highly regulated environment. The challenge is to provide developers with flexible, AI-native tools while ensuring that agentic workflows do not bypass security protocols or introduce vulnerabilities. Prepare by demonstrating how you have implemented 'paved paths' that enforce security by default without hindering developer speed.
Managing the Limitations of Coding Agents
While you must drive AI adoption, you are ultimately accountable for the quality and security of the code produced. You will face the difficulty of validating AI-generated output at scale. Prepare to discuss your framework for human-in-the-loop review processes and how you mentor teams to recognize and mitigate AI hallucinations or insecure code patterns.

Practice your answers

Technical practice

Architecting Agentic SDLC Workflows

What to coverExplain how you would integrate coding agents into an existing CI/CD pipeline while maintaining security and quality. Discuss the importance of human-in-the-loop review processes and how to validate AI-generated code before it reaches production.

Balancing Developer Autonomy with Governance

What to coverHow do you design a platform that provides developers with self-service capabilities while ensuring compliance with enterprise security, IAM, and network segmentation policies? Focus on the concept of 'paved paths' and how to enforce guardrails without hindering velocity.

Context Engineering for AI Coding Agents

What to coverDescribe your approach to context engineering to improve the accuracy of AI coding agents. Discuss how you manage repository metadata, documentation, and codebase structure to ensure agents have the necessary information to perform complex tasks.

Infrastructure as Code (IaC) and GitOps at Scale

What to coverDiscuss the trade-offs between using Terraform versus AWS CloudFormation for managing complex EKS/ECS environments. Explain how you would implement GitOps practices to ensure infrastructure consistency and drift detection.

Containerized Development and Devcontainers

What to coverHow do you optimize the developer experience using devcontainers? Address challenges related to image build pipelines, dependency management, and ensuring that local development environments mirror production configurations.

Observability in Agentic Platforms

What to coverWhat metrics would you track to measure the success of an agentic cloud development platform? Explain how you would monitor agent performance, resource utilization, and the impact on overall software engineering velocity.

MCP (Model Context Protocol) Integrations

What to coverHow would you leverage MCP to connect AI agents with enterprise services like Jira, Confluence, or internal APIs? Discuss the architectural considerations for secure, scalable integrations between agents and existing toolchains.

Managing Distributed Systems on AWS

What to coverGiven the requirement for high availability, how do you manage networking and service discovery in an EKS/ECS environment? Explain your strategy for handling cross-account IAM roles and VPC security in a regulated financial environment.

Behavioural practice

Driving Technical Adoption Across Teams

What to coverDescribe a time you introduced a new tool or practice to a large engineering organization. How did you handle resistance, manage stakeholder expectations, and measure the success of the adoption?

Prioritizing a Product Backlog

What to coverAs a Product Engineer, how do you balance the need for new feature development with technical debt and platform maintenance? Provide an example of how you made a difficult prioritization decision based on user feedback or business impact.

Managing Cross-Functional Stakeholders

What to coverTell me about a situation where you had to align conflicting requirements between security, infrastructure, and product teams. How did you facilitate the conversation to reach a consensus that satisfied enterprise governance while meeting developer needs?

Learning and Adapting to AI-Native Practices

What to coverDescribe your personal journey in adopting AI-native development. How have you evolved your own engineering workflow to incorporate coding agents, and how do you stay updated on the rapidly changing AI landscape?

Sharpen your knowledge

Topics to prepare

Agentic Software Development Lifecycle (SDLC)
The role requires integrating AI coding agents into the full SDLC. Revise by mapping out how agents can be applied to specific stages like requirements gathering, code generation, testing, and security scanning. Practice identifying the limitations of AI-generated code and defining human-in-the-loop review workflows to ensure production-grade quality.
Platform Engineering Governance
Focus on balancing developer autonomy with enterprise security and compliance. Review strategies for creating 'paved paths' that allow developers to move quickly while adhering to strict infrastructure, networking, and IAM guardrails. Consider how to measure developer productivity and platform adoption through metrics.

Skills to revise

Infrastructure as Code (IaC) and AWS Automation
Demonstrate proficiency in Terraform or AWS CloudFormation by designing a modular deployment pattern for EKS or ECS. Practice writing IaC templates that incorporate security best practices, such as least-privilege IAM roles and VPC network segmentation, which are critical for regulated environments.
Context Engineering for AI Agents
Develop expertise in providing high-quality context to coding agents. Practice creating structured documentation, clear coding standards, and reference workflows that agents can use to generate more accurate and compliant code. Explore how to integrate these practices into IDE extensions or developer toolchains.
Containerized Development and Devcontainers
Refine your ability to manage containerized development environments. Practice configuring devcontainer features to ensure consistent tooling, SDKs, and CLI versions across a large engineering team, ensuring that the local development experience mirrors the production environment.

Your preparation checklist

Prepare an Agentic SDLC Case Study
Document a specific project where you integrated coding agents into the software development lifecycle. Focus on how you validated AI-generated code, managed context engineering, and ensured security compliance while improving developer velocity.
Map AWS Infrastructure and Governance Experience
Prepare to discuss your experience managing EKS/ECS clusters and VPC networking within regulated environments. Be ready to explain how you used Terraform or CloudFormation to enforce security guardrails and least-privilege IAM policies.
Develop a Platform Engineering Philosophy
Formulate your approach to balancing developer autonomy with enterprise governance. Prepare examples of how you have managed a product backlog for internal developer tools, measured adoption, and iterated based on user feedback.
Draft Technical Enablement Strategies
Prepare a brief outline of how you would drive AI-native adoption across a large organization. Include how you would create reference workflows, documentation, and enablement sessions to help other engineers safely adopt agentic tools.
Formulate Strategic Questions for the Team
Prepare thoughtful questions regarding the current maturity of GIC's agentic cloud development platform, the primary security challenges in their current CI/CD pipelines, and how the team balances rapid innovation with the firm's Prudence value.

Availability last checked: 19 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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