Staff Engineer, Cloud Platform

Accountabilities: Define and drive the technical strategy for platform observability across AWS and GCP, covering metrics, logs, traces, and events. Build, maintain, and improve observability infrastructure using Datadog, Prometheus, Grafana, and OpenTelemetry, including shared instrumentation libraries and collectors. Partner with service owners to establish meaningful Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets, supported by dashboards and burn-rate alerts. Improve alert quality by reducing noise, ensuring alerts are actionable, correctly routed, and supported by clear runbooks. Reduce mean time to detect (MTTD) and mean time to recover (MTTR) through better tracing, event correlation, and incident tooling. Manage observability costs through cardinality controls, log-volume optimization, sampling, and retention strategies. Lead cloud FinOps initiatives, establishing tagging standards, cost allocation, and showback reporting across teams and services. Identify and implement cloud cost savings through resource right-sizing, autoscaling, spot capacity, storage optimization, idle-resource cleanup, and data-transfer reduction. Develop cloud commitment strategies, including Savings Plans, Reserved Instances, and committed-use discounts, in partnership with finance. Build cost-management automation and guardrails, including budget alerts, anomaly detection, and policy-as-code controls. Define unit economics, such as cost per customer or device, and integrate cost considerations into engineering design decisions. Collaborate with finance on cloud forecasting and budgeting, translating technical spending data into clear recommendations for leadership. Own the end-to-end incident management framework, including severity definitions, on-call rotations, escalation paths, communications, and supporting tools. Lead major incident response as an incident commander or senior escalation point, coordinating technical teams and keeping customers and leadership informed. Conduct root cause analyses for significant incidents and ensure corrective actions are completed to prevent recurrence. Develop AI agents and automation that correlate alerts, logs, traces, and recent changes to accelerate root cause identification. Build safe self-healing capabilities that detect and remediate known issues proactively, with appropriate safeguards and human approval where necessary. Define and track operational health metrics, including MTTD, MTTR, recurring incidents, and on-call workload. Own business continuity and disaster recovery strategy for the cloud platform, defining Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs) with product and leadership teams. Design and implement disaster recovery environments across AWS and GCP, covering replication, backups, failover, and failback. Plan and execute regular disaster recovery tests and failover exercises, document outcomes, and drive remediation of identified gaps. Maintain recovery automation, disaster recovery runbooks, and business continuity documentation, supporting audits and customer evidence requests. Write production-quality Go or Python code for platform tooling, exporters, data pipelines, and operational automation. Work with customer support teams to turn tickets and escalations into improved monitoring, actionable alerts, and lasting technical fixes. Partner with product engineering teams to promote reliability, recoverability, and cost-conscious system design. Produce technical design documents, review architecture across engineering teams, and mentor engineers in observability, reliability, and FinOps practices. Requirements: 10+ years of software engineering experience, including at least 4 years in platform engineering, Site Reliability Engineering (SRE), or infrastructure roles supporting large-scale, 24/7 SaaS environments. Extensive hands-on experience designing and operating observability solutions using Datadog, Prometheus, Grafana, and/or OpenTelemetry. Strong understanding of service instrumentation, SLO design, error budgets, alerting strategies, and production monitoring. Demonstrated success in reducing cloud infrastructure costs, with measurable results and the ability to explain the savings achieved. Practical experience with AWS cost-management tools such as AWS Cost Explorer, Cost and Usage Reports (CUR), Kubecost, or equivalent platforms, including cloud commitment planning. Strong software development skills in Go or Python, with experience building production-grade tools and automation rather than relying solely on scripts or dashboards. Extensive production experience with both AWS and Google Cloud Platform (GCP), infrastructure as code using Terraform, and Kubernetes. Proven experience owning on-call and incident management processes, leading major incidents, and conducting root cause analyses that result in lasting improvements. Hands-on experience building incident response or remediation automation, including AI agents or LLM-based tools for root cause analysis and automated remediation. Experience designing and testing disaster recovery strategies for production SaaS systems, including RTO/RPO targets, recovery environments, replication, and failover exercises. Software engineering background and experience working closely with customer support teams to resolve technical issues and minimize customer impact. Staff-level technical leadership, with the ability to influence multiple engineering teams, drive adoption of shared standards, and lead initiatives without direct managerial authority. Strong communication and collaboration skills, including the ability to translate cloud usage, reliability, and cost data into clear decisions for technical and business stakeholders. Bachelor's degree in Computer Science or a related discipline, or equivalent practical experience. Fluency in written and spoken English, as the organization operates across international teams. Willingness and ability to participate in assigned on-call shifts and respond to production alerts. A collaborative mindset, commitment to continuous improvement, and ability to build strong working relationships across teams. Preferred: FinOps Certified Practitioner credential or practical experience applying the FinOps Framework. Preferred: Experience with cloud cost-management platforms such as CloudHealth, Vantage, Cloudability, or AWS Compute Optimizer. Preferred: Experience building cloud cost and usage data pipelines using AWS CUR, BigQuery billing exports, Athena, or similar technologies. Preferred: Experience operating large-scale self-managed observability platforms, including Prometheus, Thanos, Mimir, Loki, or Tempo, and evaluating them against SaaS alternatives. Preferred: Exposure to eBPF-based monitoring, continuous profiling, or real-user monitoring. Preferred: Experience managing or negotiating vendor contracts related to cloud infrastructure or observability services. Preferred: Open-source contributions, technical publications, or conference presentations focused on observability or FinOps. Benefits: Fully remote working arrangement within India. Opportunity to take technical ownership of critical cloud platform capabilities in a global SaaS environment. Exposure to large-scale AWS and GCP infrastructure, modern observability technologies, FinOps, and AI-driven automation. Scope to influence platform architecture, engineering standards, reliability strategy, and cloud cost optimization across multiple teams. Collaboration with experienced engineering, product, customer support, finance, and leadership professionals. Opportunities to mentor engineers, share technical expertise, and contribute to continuous improvement. Inclusive and collaborative work culture that values diverse perspectives, innovation, and professional growth. Salary, healthcare coverage, insurance, paid leave, retirement benefits, and other specific perks are not detailed in the job description.