Role & responsibilities

- Build and maintain dashboards, alerts, SLO definitions, and runbooks across the CCOE observability stack: CloudWatch and X-Ray, Grafana / Prometheus, Dynatrace, OpenSearch (and the legacy ELK stack where it still exists), and ServiceNow ITSM
- Implement Terraform and Helm changes against the observability paved road; consume the private Terraform module library and raise small, well-scoped pull requests against shared observability modules and reference dashboards
- Partner with the Support team on incident response: tune alert routing into ServiceNow, execute runbooks, and feed lessons from incidents back into durable monitoring improvements
- Pair with senior engineers and AVPs in the Monitoring pod on noisy alert chains, missing-signal investigations, and SLO refactors; ask for help early and write down what you learn
- Embed agentic AI capabilities into the team's engineering practice (e.g., Cursor, Claude Code, Bedrock, MCP servers, agentic IaC and review workflows) and into the platform's self-service experience for internal customers
- Use agentic AI capabilities in your day-to-day observability work: AI-assisted alert triage, dashboard drafts from natural-language intent, summary of recent telemetry during incidents via MCP-backed agents, and runbook generation for known incident classes
- Operate as a hands-on mid-level cloud engineer in the pod: spend the majority of your time in Terraform code, AWS console / CLI, design documents, peer code review, and incident response execution and growth are the primary leverage points
- Personally participate in 24x7 on-call rotations as a primary responder for production incidents within the pod's scope; grow into senior responder framing over time with support from AVPs and VPs




- Consume the private Terraform module library and reference patterns to ship application-aligned infrastructure; raise small, well-scoped pull requests against shared modules and the Account Factory for Terraform (AFT) foundational base layer to improve what you use
- Partner with peer engineers, AVPs, and VPs across the Cloud Center of Excellence the five CCOE teams (Foundations, Platforms, Containers, Support, Delivery) and the five Foundations pods (Security & Governance, FinOps, Functional Design Engineering & Strategy, Network Engineering, Monitoring) to deliver pod outcomes; ask for help early and pass what you learn on to peers
- Apply the AWS Well-Architected Framework in the work you touch and drive continuous improvement against operational, security, reliability, performance, cost, and sustainability outcomes
- Participate fully in Agile / Scrum ceremonies (sprint planning, standups, backlog grooming, retrospectives) with the pod's embedded Scrum Master and partner with the enterprise EPMO / RTE on delivery commitments and dependencies
- Pursue and maintain the Engineer 2 certification path per the CCOE certification matrix AWS Certified Developer Associate, HashiCorp Certified: Terraform Associate (004), Kubernetes and Cloud Native Associate (KCNA), and Certified Kubernetes Application Developer (CKAD) progressing toward Senior Engineer over time
- 3+ years of progressive technical experience in cloud infrastructure, platform engineering, or software engineering; Bachelor's degree in Computer Science,



Engineering, or a related discipline (or equivalent work experience)
- 1+ years of hands-on production AWS in a multi-account environment with hands-on production Terraform delivered through Terraform Cloud and GitHub Actions; comfort consuming a private Terraform module library and raising well-scoped pull requests against shared modules
- Demonstrated track record of owning meaningful, well-scoped engineering work end-to-end under senior guidance — design, implementation, code review participation, and follow-through
- Experience participating in 24x7 production on-call rotations as a primary responder in a fast-paced, security-conscious environment (financial services preferred)
- Working knowledge of an enterprise observability stack — metrics, logs, traces, dashboards, and alerting — across AWS-native services (CloudWatch, X-Ray, OpenSearch) and at least one of Grafana / Prometheus, Dynatrace (or comparable APM), or the ELK stack

Preferred candidate profile

- Strong growth mindset — actively pursues the Engineer 2 certifications in the CCOE certification matrix and uses each incident, code review, and design discussion as a learning loop
- Bias toward shipping high-quality, well-tested, code-reviewed work; leaves the codebase a little better than they found it
- Asks for help early when stuck and writes down what they learn for the next engineer
- Calm primary responder during incidents; pages an AVP or VP early rather than struggling alone
- Continuous learner in cloud-native, IaC, and applied AI
- Builds high-trust relationships with peer engineers across the US and India / GCC
- Excellent written and verbal communication; can articulate what they changed and why in a explicit pull request description

📌 Engineer II - Cloud Monitoring Engineer (Hyderabad)
🏢 LPL Financials
📍 Hyderabad