12 часов назад
Senior Software Engineer (AI)
116 475 - 174 713$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Software Engineer (AI): Building and operating highly available application platforms and AI-assisted incident response systems with an accent on observability, reliability engineering, and production machine learning. Focus on designing SLIs and SLOs, developing LLM-based operational tools, analyzing distributed-system performance, and reducing MTTR through anomaly detection and automation.
Location: Atlanta, Georgia, United States; office-first culture with three days per week in the office for most roles
Annual base salary: $116,475–$174,712.50 USD for candidates based in California, Colorado, Connecticut, Nevada, New York, Rhode Island, and Washington.
Company
develops an AI-ready governance platform that combines regulatory intelligence, automation, and connected workflows for responsible data use.
What you will do
- Design, deliver, and maintain highly available and performant application platforms with Engineering, Operations, and Product teams.
- Build observability, monitoring, centralized logging, metrics, and high-signal alerting systems.
- Define and maintain SLIs, SLOs, and error budgets aligned with customer experience and product velocity.
- Automate operational processes and incident response using Python, Bash, Java, or Ruby.
- Build and operate AI-assisted incident response systems, including root-cause analysis, log summarization, and anomaly triage.
- Review architectures with product teams, identify reliability risks, and communicate findings to technical leadership and senior management.
Requirements
- Bachelor’s degree in computer science, engineering, or a related technical or business field.
- At least four years of application development experience with Java or an equivalent language, including Spring experience.
- Experience with cloud infrastructure, distributed systems at scale, Kubernetes, containers, microservices, and service meshes.
- Knowledge of application performance factors including databases, networks, CPU and memory utilization, JVM tuning, thread management, and query performance.
- Hands-on experience with observability tools such as Datadog, Prometheus, or Grafana, plus CI/CD and infrastructure-as-code tools including Terraform, Helm, Jenkins, or GitLab.
- Production experience deploying AI systems, LLM-based tools, machine-learning techniques, vector databases, embeddings, RAG architectures, and prompt evaluation for reliability workflows.
Nice to have
- Experience with chaos engineering tools such as Gremlin or Chaos Monkey.
- Background with high-traffic, product-facing services.
- Experience using incident management platforms such as PagerDuty and Datadog.
Culture & Benefits
- Office-first work environment with regular in-person collaboration.
- Healthcare coverage, flexible paid time off, equity RSUs, and annual performance bonus opportunities.
- Retirement account support and 14+ weeks of paid parental leave.
- Career development opportunities and company-paid privacy certification exam fees.
- Employee support focused on physical, mental, and emotional well-being.
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