Technical Lead, Platform Engineering (Observability)

Accountabilities:

• • Observability Platform Engineering: Design, build, operate, and continuously improve an observability platform covering metrics, logs, distributed traces, dashboards, and alerting at scale.
  • Technical Leadership: Drive the technical direction of observability capabilities, make architectural decisions, establish engineering standards, and lead initiatives from design through implementation and operation.
  • Reliability Improvement: Deliver measurable improvements in Mean Time to Detect (MTTD) and Mean Time to Mitigate (MTTM), while improving service reliability and operational resilience.
  • AI-Powered Observability: Design and implement intelligent solutions for automated anomaly detection, alert correlation, root cause analysis, and AI-assisted incident response.
  • Self-Service Tooling: Build developer-focused tooling that enables product engineering teams to independently instrument services, create dashboards, configure alerts, and adopt observability best practices.
  • Standards & SLOs: Define and champion observability standards, instrumentation practices, Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error-budget frameworks across the engineering organization.
  • Platform Optimization: Improve data collection, processing pipelines, alert quality, and operational workflows while reducing noise, unnecessary toil, and observability-related costs.
  • Cross-Functional Collaboration: Partner with SRE, Security, platform teams, and product engineering teams to ensure comprehensive system visibility and consistent reliability practices.
  • Automation: Automate recurring operational processes and workflows to increase engineering efficiency and improve the team's ability to respond to incidents.
  • Mentorship & Culture: Lead by example, mentor engineers, contribute to technical discussions, and help foster a strong engineering culture centered on collaboration, ownership, and continuous improvement.
  • Documentation: Produce high-quality technical and architectural documentation and facilitate design discussions with relevant engineering stakeholders.

  Requirements

  • Professional Experience: 9+ years of experience building, operating, and maintaining scalable production systems, with significant experience in platform engineering, infrastructure, SRE, or related disciplines.
  • Observability Expertise: Strong hands-on experience with production observability and monitoring platforms such as Datadog, Prometheus, Grafana, or equivalent technologies.
  • Distributed Systems: Deep understanding of metrics, logging, distributed tracing, instrumentation patterns, and observability data pipeline architecture.
  • Kubernetes: Proven experience deploying, operating, and troubleshooting Kubernetes-based production environments and containerized workloads.
  • Programming: Strong proficiency in Go or Python for developing infrastructure tooling, platform services, and automation.
  • Cloud & Infrastructure as Code: Experience with GCP and/or AWS and Infrastructure as Code technologies such as Terraform.
  • Alerting & Incident Detection: Demonstrated ability to design and tune alerting systems to improve signal quality, reduce alert fatigue, and accelerate incident detection.
  • Reliability Engineering: Strong understanding of SLIs, SLOs, error budgets, and modern reliability engineering practices.
  • Developer Platforms: Experience building internal platforms, tools, or self-service capabilities that improve developer productivity and engineering workflows.
  • Communication: Strong written and verbal communication skills, with the ability to produce design documentation, explain complex technical concepts, and lead technical discussions.
  • Technical Leadership: Proven ability to influence technical direction, mentor engineers, make sound architectural decisions, and drive initiatives across teams.
  • AI & Advanced Observability: Experience applying AI or machine learning to observability use cases such as anomaly detection, alert correlation, or root cause analysis is preferred.
  • Large-Scale Systems: Experience supporting observability across large distributed environments, ideally involving hundreds of microservices.
  • OpenTelemetry: Hands-on experience with OpenTelemetry for instrumentation and telemetry collection is an advantage.
  • Observability Cost Optimization: Experience with sampling strategies, data tiering, pipeline optimization, or other approaches to controlling observability costs at scale is preferred.
  • Developer Experience: Passion for improving engineering productivity through better platform tooling, automation, and self-service capabilities.
  • Open Source: Contributions to or active participation in open-source observability communities are a plus.
  • Incident Management: Experience with incident management processes, tooling, and operational response practices is desirable.

  Benefits

  • Full-time employment with the opportunity to work on large-scale platform and observability challenges.
  • Hybrid work model with 2 days per week working from the office and 3 days remotely.
  • Bengaluru-based office environment with opportunities for collaboration and team engagement.
  • Opportunity to shape observability practices across a complex, distributed engineering environment.
  • Exposure to advanced technologies spanning cloud infrastructure, Kubernetes, AI-powered operations, distributed systems, and developer platforms.
  • Strong opportunities for technical leadership, mentoring, and career development.
  • Collaborative environment involving platform engineering, SRE, security, and product engineering teams.
  • Opportunity to directly improve engineering productivity, system reliability, and incident response at scale.
  • Professional environment focused on innovation, continuous improvement, collaboration, and high engineering standards.