Senior DevOps / Platform Reliability Engineer

Zingtree is the next-generation intelligent process automation platform reimagining customer experience operations for the world’s top support leaders. With 500+ customers, including Optum, Corpay, Sony, SharkNinja, and Allianz, we transform self-service, surface automation opportunities, and turn every agent into an expert.

We’re hiring a Senior DevOps / Platform Reliability Engineer to own the platform that powers our agentic CX product. You’ll build the CI/CD, infrastructure, and observability backbone that enables us to ship multi-agent systems safely to enterprise customers.

If you want to operate a production AI platform and use AI to help operate it, this role is for you.

In this role, you will collaborate with development, operations, and infrastructure teams to automate and streamline processes, build and maintain tools for deployment, monitoring, and operations, and troubleshoot issues across development and production environments.

• →

  Design and operate auto-remediation agents for common production toil such as certificate rotation, noisy pods, infrastructure drift, and flaky CI pipelines, with human-in-the-loop (HITL) controls for any destructive or customer-impacting actions.

• →

  Use LLMs for incident triage and root cause analysis, including log and trace summarization, signal correlation, and first-draft postmortems that are always reviewed by humans.

• →

  Connect AI agents to internal systems through the Model Context Protocol (MCP), including GitHub, Jira, PagerDuty, AWS, Kubernetes, Terraform, and related platforms, using scoped credentials, audit logging, and allow-listed access.

• →

  Apply AI-driven observability techniques, including anomaly detection on metrics, LLM-based log clustering, and alert deduplication and summarization on top of Prometheus and OpenTelemetry.

• →

  Establish operational guardrails such as prompt/version pinning, evaluation frameworks for agent behavior, cost and rate-limit controls, policy-as-code (OPA/Conftest) for AI-generated infrastructure changes, and clearly defined blast-radius controls.

• →

  Define best practices for AI coding assistants such as GitHub Copilot, Claude, and Amazon Q in infrastructure repositories, including review workflows, prompt design, and restrictions on auto-merged changes.

• →

  Treat AI components as production systems with SLOs, observability, on-call readiness, runbooks, and rollback strategies for agents and prompts.

• 5+ years of experience in DevOps, SRE, or Platform Engineering operating production systems on AWS.

• Strong experience with CI/CD pipelines and tools such as GitHub Actions, GitLab CI, Jenkins, or CircleCI.

• Hands-on experience operating production EKS environments, including autoscaling, ingress, secrets management, and cluster upgrades.

• Strong AWS networking experience, including multi-account VPC design, subnets, routing, security groups, NACLs, Route 53, ACM, and load balancers.

• Deep experience with Terraform and GitHub Actions, ideally using OIDC-based cloud authentication.

• Experience with Aurora/RDS MySQL, Redis (ElastiCache), and S3, including backups, PITR, migrations, and lifecycle management.

• Strong observability experience using Prometheus, Grafana, and OpenTelemetry.

• Experience operating Argo CD at scale.

• Experience with Infrastructure as Code tools such as Terraform, CloudFormation, or Ansible.

• Experience managing Cloudflare services including WAF, Bot Management, Rate Limiting, and Zero Trust / Access, along with CloudFront.

• Experience operating Kafka/MSK at scale, including topics, consumer groups, and schema registries.

• Experience with Lambda and event-driven architectures.

• Comfortable working with Python, Bash, and Linux systems.

• Strong understanding of security best practices across IAM, KMS, secrets management, networking, and software supply chain security.

• Familiarity with vulnerability scanning and compliance tooling.

• Experience operating LLM or ML workloads in production, including LiteLLM, Bedrock, pgvector, prompt caching, or evaluation systems.

• Experience building or integrating MCP servers or deploying agent frameworks such as LangGraph or CrewAI in production environments.

We are doers. We move quickly with purpose, take smart risks, learn fast, and focus on outcomes that benefit our customers and the business.

We win as a team. We care deeply about our customers and employees, helping each other achieve professional growth and meaningful impact.

When we commit, we deliver. We operate with integrity, accountability, and high standards.

We are learners. We continuously grow our knowledge, share expertise, and apply it to create meaningful results.

We communicate openly, honestly, and respectfully. We share information that matters and build trusted relationships through clarity and empathy.