Sr Software Engineer Syseng

Overview

Build and operate an AI-driven observability and reliability platform for enterprise-scale environments, combining SRE, platform engineering, and applied AI/ML.

What you'll do

• Design, implement, and operate enterprise observability solutions using Dynatrace, including logs, metrics, traces, and RUM.
• Define golden signals, SLOs, SLIs, and error budgets for critical applications and infrastructure.
• Create dynamic and adaptive alerting strategies to reduce noise and improve signal quality.
• Partner with application teams to embed reliability and observability standards into services from design through production.
• Build and deploy AI/ML-powered agents that analyze Dynatrace logs and metrics, historical incident data, and behavioral and anomaly patterns.
• Implement predictive monitoring and anomaly detection using statistical models or ML techniques.
• Automate alert triage, correlation, and root cause analysis (RCA) using AI-driven approaches.
• Continuously improve models based on operational feedback and outcomes.
• Design and implement self-healing systems that automatically restart or rescale services, redirect traffic, roll back failed deployments, and trigger remediation workflows.
• Integrate automated recovery actions with CI/CD pipelines, runbooks, and orchestration tools.
• Ensure recovery mechanisms are safe, auditable, and compliant with enterprise governance.
• Lead incident response, post-incident reviews, and root cause analysis.
• Establish runbooks, automated remediation playbooks, and operational standards.
• Drive reductions in MTTR, incident frequency, and operational toil.
• Participate in on-call rotations and help build a sustainable on-call culture.
• Work with cloud and on-prem infrastructure teams to improve reliability at scale.
• Build automation using Infrastructure as Code (IaC) practices.
• Ensure systems meet security, compliance, and resiliency requirements expected in financial or regulated environments.

What you'll need

• 4+ years of experience in SRE, DevOps, Platform Engineering, or Production Operations.
• Strong experience designing and operating highly available, distributed systems.
• Hands-on expertise with monitoring and observability platforms.
• Linux-based systems and networking fundamentals.
• Deep understanding of SLOs, SLIs, error budgets, and reliability trade-offs.
• Proficiency in at least one programming language such as Python, Go, Java, or similar.
• Strong scripting experience (Python, Bash, etc.) for automation and tooling.
• Experience with Infrastructure as Code (Terraform, CloudFormation, or similar).
• Experience building or integrating AI/ML models for operational use cases such as anomaly detection, log analytics, or predictive alerts.
• Familiarity with ML pipelines, feature extraction, and model lifecycle management.
• Familiarity with rule-based and ML hybrid approaches for production systems.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Strong knowledge of Kubernetes and container orchestration.
• Strong knowledge of CI/CD pipelines and deployment automation.
• Understanding of scalable architecture patterns and failure modes in cloud-native systems.
• Ability to adapt, learn new technologies, develop new processes, and improve procedures.
• Excellent verbal and written communication skills.
• Ability to perform problem-solving using logic and creative thought processes to resolve complex technical problems.

Nice to have

• Experience integrating AI workflows into monitoring and alerting platforms is highly valued.
• Strong preference for Dynatrace experience.

Details

• Location: Hyderabad.