Principal Platform Engineer

Weekday AI

This role is for one of Weekday’s clients

Min Experience: 12+ years
Location: Bengaluru
JobType: full-time

Requirements

Key Responsibilities

Platform Architecture & Strategy

Architect and evolve a unified, developer-centric platform across multi-cloud environments (AWS, Azure, and/or GCP).
Bridge the gap between application logic and infrastructure, ensuring seamless integration and high-performance execution.

AIOps & Intelligent Automation

Lead the AIOps transformation: Architect and implement AI-driven systems for predictive scaling, intelligent incident response, and automated root-cause analysis.
Leverage LLMs and ML models to automate Infrastructure-as-Code (IaC) generation, security remediation, and complex diagnostic workflows.
Implement log anomaly detection and predictive observability to transition from reactive to proactive system management.

CI/CD & Developer Experience (DevEx)

Design high-velocity, "paved-road" deployment pipelines that empower engineers to ship code safely.
Drive the adoption of AI-assisted development tools to accelerate the software delivery lifecycle.

Kubernetes & Scalability

Lead the architecture of global-scale Kubernetes environments, focusing on multi-tenancy, security, and service mesh performance.
Optimize system performance under extreme traffic, ensuring 99.99% availability through advanced capacity planning.

FinOps & Governance

Implement advanced FinOps practices to optimize cloud spend, utilizing AI-driven forecasting to eliminate waste.
Establish strong human-in-the-loop governance for all AI-automated infrastructure changes.

What We’re Looking For

Experience & Expertise

12 to 15 years of experience in Software Engineering, Infrastructure, and Platform Engineering.
Dual-Competency: Proven track record of architecting large-scale applications and managing the underlying cloud infrastructure.
Autonomy: Proven ability to troubleshoot issues across the entire stack—from application code and API performance to network latency and container orchestration.

Technical & Problem-Solving Skills

Deep expertise in multi-cloud architecture and distributed systems design.
Expert-level knowledge of Kubernetes, service meshes (e.g., Istio, Linkerd), and cloud-native observability.
AIOps Proficiency: Demonstrated experience implementing AI/ML-driven operational workflows (e.g., automated diagnostics, predictive maintenance).

Collaboration & Leadership

Experience leading and mentoring teams in a global, cross-functional environment.
Ability to influence stakeholders and align technical strategy with high-level business objectives.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Nice to Have

Experience training or fine-tuning models for infrastructure automation.
Contributions to open-source projects related to Cloud-Native or AI tooling.
Deep knowledge of modern observability stacks (Prometheus, Grafana, Honeycomb, Datadog).
Experience with advanced infrastructure security (Zero Trust, Policy-as-Code).

Microsoft Azure, GCP, Kubernetes

Docker and Kubernetes, Application, Full-Stack Development