Member of Technical Staff

About the role

This opportunity represents a specialized infrastructure architect position focused on the deployment and scaling of AI engineering platforms within cloud-native environments. You will own the design and integrity of the systems that power AI-assisted development workflows, ensuring they meet stringent reliability and security standards. The role requires translating ambiguous product ambitions into concrete, measurable infrastructure strategies that directly support engineering productivity. You will be the primary technical owner responsible for the stability and performance of the infrastructure stack that runs complex AI workloads. This position demands a deep understanding of distributed systems and the ability to operate at the intersection of development and platform engineering. You will act as a bridge between strategic architectural vision and the day-to-day operational realities of running AI services in production. The position is critical for organizations seeking to move from experimental AI usage to governed, enterprise-scale adoption.

Key facts

What you'll do

• Architect and secure the foundational cloud infrastructure for container orchestration and continuous integration and delivery pipelines across GCP and AWS environments.
• Establish secure networking and storage frameworks using Infrastructure as Code solutions such as Terraform and OpenTofu to maintain environment consistency.
• Implement comprehensive observability mechanisms, log aggregation, and real-time alerting to identify and prevent state drift before it impacts AI services.
• Orchestrate the migration of existing infrastructure into a clean, immutable architecture while minimizing production risk and ensuring continuity.
• Construct and refine deployment pipelines that align with rapidly evolving product requirements and support dynamic AI development loops.
• Configure monitoring and tracing specifically tailored for AI workloads to uphold reliability during complex, multi-step execution scenarios.
• Collaborate closely with product teams to ensure infrastructure capabilities keep pace with feature experiments, usage trends, and evolving business needs.
• Author detailed operational runbooks and environment standards to support secure, scalable, and repeatable growth across engineering teams.
• Quantify the utilization of AI coding instruments such as Cursor, Claude Code, and GitHub Copilot to provide data-driven insights on engineering effectiveness.
• Provide leadership with board-ready, defensible data and metrics to demonstrate the return on investment of AI tooling and infrastructure initiatives.
• Drive the standardization of operational practices to reduce technical debt and improve the long-term maintainability of the platform.
• Ensure that all infrastructure components are designed with security, scalability, and cost-efficiency as core principles.
• Support the development of best practices for prompt engineering and AI tooling workflows through technical guidance and platform enablement.
• Act as a technical authority to resolve complex infrastructure issues that arise during the operation of AI-native development platforms.

Requirements

• Bring a minimum of two years of hands-on infrastructure experience in high-stakes, reliability-focused environments where uptime is critical.
• Demonstrate a strong grasp of operating system internals, network layers, and distributed systems principles that underpin modern cloud platforms.
• Show foundational knowledge of infrastructure and automation tools, with priority given to practical ability over specific tool certification.
• Exhibit comfort with fast-paced, ambiguous, and shifting technical environments where requirements evolve frequently.
• Prove the capacity to work effectively under uncertainty and adapt to evolving technical requirements without reliance on rigid processes.
• Display strong problem-solving skills and a methodical approach to diagnosing and resolving complex infrastructure failures.
• Communicate technical concepts clearly to both technical and non-technical stakeholders, including engineering leadership and product managers.
• Commit to adhering to established security policies and compliance standards relevant to cloud infrastructure management.
• Be willing to travel as required for team collaboration, stakeholder meetings, or client engagements related to platform deployment.
• Be available for full-time employment in Bangalore, ensuring alignment with local working hours and operational support needs.

Nice to have

• Direct experience with prompt engineering and AI tooling, including Cursor, Claude Code, and GitHub Copilot, to better understand platform usage patterns.

Practical notes

This role is offered as a full-time engagement based in Bangalore. Compensation is fixed at 280,000 USD on an annual basis. Candidates should be prepared for potential travel requirements and availability for standard working hours within the region. Exact details regarding location, schedule, and compliance may vary and should be verified directly with the hiring team. There are no specific visa sponsorship details outlined at this time, and candidates must ensure they meet local employment eligibility criteria.