About this Principal Platform Engineer role at 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).
Must-have skills
Microsoft Azure, GCP, Kubernetes
Good-to-have skills
Docker and Kubernetes, Application, Full-Stack Development