Senior Cloud Engineer, Observability

Bayer•Tulsa, OK

2d•$130,000 - $180,000•Remote

About The Position

At Bayer Crop Science’s digital farming arm, we advance regenerative agriculture and technology breakthroughs using agronomic science, data science, engineering, and real-world farming experience. Our shared AWS platform enables hundreds of engineers to ship secure, reliable software faster. We’re looking for an entrepreneurial builder who treats observability as a product: paved roads for telemetry, opinionated patterns for dashboards/alerts, and a relentless focus on improving signal quality and reducing time-to-detect/time-to-recover. You’ll partner with delivery teams, Security, and Data to standardize how we instrument services, monitor reliability, and learn from production.

Requirements

Bachelor’s in computer science/engineering or equivalent experience.
5+ years hands-on AWS experience operating production workloads.
Deep practical experience with observability in production, including: Datadog and/or CloudWatch (dashboards, monitors/alerts, log search, correlation)
Designing actionable alerts (noise reduction, ownership, runbook-first alerts)
Defining/using SLIs/SLOs and reliability metrics to drive behavior
Strong proficiency with Infrastructure as Code (Terraform; CloudFormation a plus).
Strong programming for automation/tooling (Python, Go, or similar).
Solid grasp of cloud architecture, networking, and security fundamentals.

Nice To Haves

Experience productizing observability enablement (templates, golden paths, standards, onboarding workflows).
CI/CD at scale (GitLab pipelines), including integrating reliability/telemetry guardrails into delivery workflows.
Logging/telemetry platforms beyond CloudWatch/Datadog (e.g., ELK/OpenSearch) and experience managing scale concerns (volume, retention, cardinality).
Container platforms (ECS/EKS) and common AWS data services (RDS/Aurora, S3/lake patterns, MSK/Kinesis).
FinOps experience related to observability (tagging, allocation, optimizing telemetry cost).
Relevant AWS certifications and excellent communication skills.

Responsibilities

Be the hands-on SME for our observability toolchain (e.g., Datadog, CloudWatch, OpenSearch), including log pipelines, tracing/telemetry standards, and platform templates.
Run office hours, produce exemplars, and pair with teams to implement “known-good” instrumentation and alerting.
Triage and resolve observability-related platform requests (new service onboarding, log/metric gaps, noisy alerts, dashboard standards) with clear ownership and measurable outcomes.
Establish and operationalize SLIs/SLOs for key platform components and enable teams to define service SLOs without reinventing the wheel.
Maintain opinionated “golden paths” for Logging (standard fields/tags, retention, routing, searchability), Metrics (naming conventions, cardinality guardrails, standard RED/USE views), Tracing (service maps, critical spans, propagation standards), and Dashboards (starter dashboards by service type + curated views for platform reliability).
Provide reusable templates for alerting patterns (latency, error-rate, saturation, dependency failures), tuned for actionable paging vs. noise.
Reduce MTTR by improving detection, triage paths, runbooks, and “what changed” visibility.
Drive reliability reviews focused on observability gaps: missing signals, unclear ownership, bad alerts, and uninstrumented failure modes.
Partner with delivery teams to turn recurring incidents into durable fixes (instrumentation + alerting + automation + documentation).
Embed observability checks into CI/CD and platform workflows (e.g., telemetry guardrails, dashboard/monitor templates, logging standards checks).
Partner with Security/Compliance to ensure telemetry supports auditability and incident investigation without ad-hoc effort.
Define and report platform observability KPIs: alert noise rate, % actionable alerts, MTTA/MTTR trends, onboarding time to “fully observable,” runbook coverage, incident recurrence.
Run lightweight experiments to improve signal quality (threshold tuning, monitor redesign, dashboard UX), and ship improvements like a product owner.
Create cost-aware telemetry standards (log volume controls, metric cardinality guidance, sampling strategies, retention tiers).
Help teams optimize spend while improving reliability outcomes (“cheaper + better” logging/metrics patterns).
Serve as a trusted partner to delivery units, Security, and Data—turning pain points into paved-road improvements.
Mentor engineers and uplift organizational practices for incident response, reliability signals, and operational excellence.