DevOps Engineer

About Sayari:

Sayari is the judgment infrastructure for trustworthy AI in economic security and commercial risk. The Sayari Commercial World Model resolves 11.7B+ primary-source records from 250+ jurisdictions forming the ground truth of global commerce. A Judgment Ontology, encoding over a decade of investigative tradecraft, and Superconductor, an agentic orchestration platform, deliver AI that reasons like an expert analyst, shows its work, and traces every finding to its source. Trusted by U.S. Customs and Border Protection, HM Revenue & Customs, and Fortune 500 enterprises, Sayari is used by thousands of professionals across 35+ countries to secure supply chains and dismantle illicit networks. Headquartered in Washington, D.C., with offices in London, Singapore, Tokyo, and Tel Aviv.

JOB RESPONSIBILITIES

• AI-Enhanced Engineering: Act as a force multiplier by using modern AI tools to accelerate coding, debugging, and process automation.
• Automate FinOps Governance: Go beyond monthly reports by implementing \"governance-as-code.\" Write automated policies and scripts that actively manage resource lifecycles, tag compliance, and prevent wasteful cloud spend before it happens.
• Advance Infrastructure as Code: Manage and scale our IaC (Terraform), with modular, reusable patterns that allow developers to provision what they need within guardrails.

SKILLS & EXPERIENCE

Required:

• Deep production experience with GCP or AWS. You understand how to architect for resilience and security in a multi-cloud environment.
• Expert-level proficiency with Terraform. You don't just run plans; you write modular, scalable code from scratch.
• Hands-on experience building CI/CD pipelines with GitHub Actions and managing deployments using tools such as ArgoCD or Flux.
• Strong scripting/coding ability in Bash and Python.
• Proven experience automating cloud cost controls. You understand how to implement cost attribution strategies and automated cleanup policies.
• Experience provisioning and securing Snowflake environments from an infrastructure perspective.
• Experience using AI tools to accelerate coding, debugging, process automation, and documentation.
• Familiarity with Site Reliability Engineering principles, including defining SLIs/SLOs, managing error budgets, and structured incident response.

Preferred:

• Experience with AI/LLM infrastructure or GPU workloads.
• Familiarity with distributed data stores (Apache Cassandra, JanusGraph) or orchestration tools (Cadence).
• Experience with tools such as Terragrunt and Atlantis for advanced IaC workflows.
• Familiarity with tools such as Elastic Cloud or Datadog for monitoring and observability.
• Experience building or managing Internal Developer Portals.