Description
manage a team that designs, develops, troubleshoots and debugs software programs for databases, applications, tools, networks etc.
responsibilities
as a manager, you will lead people and apply your knowledge of sre to manage tasks associated with cloud operations, developing, debugging or designing software applications, operating systems and databases according to provided design specifications. Build enhancements within an existing software architecture and occasionally suggest improvements to the architecture.
key responsibilities
- end-to-end service ownership: design for telemetry, security, resiliency, scalability, and performance; lead sizing/architecture; drive service health reviews and process simplification.
- incident management and prevention: lead postmortems/rcas, coordinate fixes, define repair items, and implement data-driven prevention and continuous improvement.
- ai/ml and genai delivery: design and integrate solutions with llms, rag, agentic workflows, and conversational ai; build low-latency model serving and retraining pipelines.
- application engineering: develop performant microservices for distributed, containerized, cloud-native systems.
- automation: eliminate toil by automating operational workflows, recovery procedures, code delivery, and configuration management; build internal tools and reusable scripts/services to accelerate delivery and reduce errors.
- observability: define and implement monitoring, logging, alerting, and tracing strategies; establish slos/slis/error budgets; improve diagnostics and performance visibility for rapid triage.
- cross-functional collaboration: partner with product, operations, and data teams to translate requirements into secure, scalable solutions; communicate effectively with technical and non-technical stakeholders.
minimum qualifications
- bs/ms in computer science or related field; 10+ years of software engineering in cloud environments.
- strong in distributed systems/microservices using java / python; sql/data modeling; python for ai/automation.
- sre/devops expertise: systems and networking fundamentals, application security, observability, performance analysis, and incident response.
- proven sdlc excellence: code quality, reviews, version control, ci/cd, testing, and release engineering.
- excellent written and verbal communication; english fluency.
preferred/technical skills
- ai/ml/genai: experience with foundational models, rag, agentic architectures; model deployment, optimization, monitoring, and retraining.
- cloud and containers: experience with containerization, orchestration, and resilient, fault-tolerant microservices.
- observability: hands-on experience designing dashboards, alerts, traces, logs, and metrics; defining slos/slis and error budgets; on-call readiness and runbook quality.
- operations: performance tuning across java / python and sql for large-scale enterprise applications; strong linux/unix expertise; capacity planning and reliability reviews.
- automation and scripting: proficiency in scripting to automate operational workflows, build tooling, and ci/cd tasks (e.g., shell scripting, python, configuration-as-code, task runners).
- familiarity with enterprise erp applications and standard devops tooling and practices.
qualifications
career level - m2