Infrastructure Development Engineer

Infrastructure Development Engineer

W2 Contract

Salary Range: $124,800 - $145,600 per year

Location: Austin, TX - Remote Role

Duties and Responsibilities:

Platform Reliability & Operations

• Own end-to-end reliability for our AI Agent Platform across all environments (Dev, Staging, Production).
• Maintain and optimize EKS clusters, databases, and LangGraph/LangSmith environments.
• Implement and manage proactive monitoring, alerting, and tracing systems across platform components.
• Drive root-cause analysis (RCA) and implement incident prevention automations.

Observability & Tooling

• Deliver a unified observability strategy across services using logging, metrics, and distributed tracing.
• Lead the migration from DataDog to Mosaic for dashboards and alerting.
• Develop self-healing automation and smoke tests to validate post-deployment system health.
• Ensure visibility into latency, availability, and error budgets (SLOs/SLIs).

Support & Incident Management

• Own the AI platform Support Channel - triage issues, answer platform questions, and guide onboarding.
• Provide L1/L2 triage during business hours; coordinate after-hours escalation with the core team.
• Establish structured runbooks, escalation policies, and post-incident review processes.

Deployment & Environment Consistency

• Standardize infrastructure and CI/CD practices across environments.
• Partner with platform and ML engineers to streamline release pipelines, security policies, and service configurations.
• Ensure consistent rollout of new features and agent services with minimal downtime.

Automation & Continuous Improvement

• Develop Python or Go utilities to automate deployment, monitoring, and maintenance tasks.
• Build tooling for alert correlation, system diagnostics, and capacity forecasting.
• Continuously evaluate new tools and frameworks to improve operational efficiency.

Requirements and Qualifications:

• 4+ years of experience as an SRE, DevOps Engineer, or Platform Engineer in cloud environments
• Deep expertise with Kubernetes (EKS/GKE), CI/CD pipelines, and infrastructure automation.
• Proficiency with observability tools such as Grafana, Prometheus, DataDog, Splunk, or OpenTelemetry.
• Experience in at least one modern programming language (Python, Go, or Rust).
• Strong understanding of incident management, SLAs/SLOs, and post-mortem practices.
• Excellent communication and collaboration skills; ability to work across platforms, AI, and data teams.

Preferred Qualifications:

• Experience operating AI/ML workloads (LangGraph, LangChain, or distributed compute systems like Ray).
• Familiarity with LLM-based infrastructure and AI observability tooling.
• Prior experience in managed service transitions or vendor-to-product operating model shifts.
• Exposure to Azure or AWS cloud ecosystems, Terraform, and GitOps workflows (ArgoCD/Flux).

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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