Saaf Finance

Senior DevOps Engineer

Vaga remota de Senior DevOps Engineer com fit claro de localização do candidato.

Publicada14 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

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Conteúdo da vaga extraído em seções para revisão mais rápida.

Design, build, and maintain production-grade AWS infrastructure using Infrastructure-as-Code (Terraform preferred).
Architect and manage serverless and containerized environments that balance cost, performance, and reliability.
Implement and maintain networking, security groups, IAM policies, and cloud resource configurations following least-privilege principles.

Own and evolve the CI/CD pipeline ecosystem, primarily using GitHub Actions, to enable fast, safe, and repeatable deployments.
Implement deployment strategies (blue-green, canary, rolling) that minimize risk and downtime.
Automate build, test, and release workflows across multiple services and environments.

Leverage AI-assisted tools (code generation, intelligent autocomplete, automated IaC authoring) as a regular part of your infrastructure workflow to accelerate delivery and reduce configuration errors.
Use AI tools to support incident diagnosis, log analysis, runbook generation, and documentation of infrastructure decisions.
Evaluate and integrate emerging AI tools and practices into the team's DevOps processes.
Build and support the infrastructure layer for agentic workflows, including compute orchestration, autoscaling, and cost-efficient execution of AI-powered automation.

Design and maintain monitoring, logging, and alerting systems that provide clear visibility into platform health and performance.
Implement distributed tracing and structured logging across services and multi-step workflows.
Lead incident response, conduct post-mortems, and drive reliability improvements based on findings.

Apply cloud security best practices across all infrastructure, including secrets management, encryption, network segmentation, and access controls.
Design secure secrets and configuration management for agentic processes, including API keys, model tokens, and external service credentials.
Ensure infrastructure meets financial regulatory and compliance requirements with full auditability.

Support and maintain infrastructure for data engineering workflows, including Snowflake environments, ETL/ELT pipelines, and dbt execution.
Manage serverless event-driven pipelines and orchestration tools (Step Functions, Temporal, or similar).

Collaborate with product engineers, data engineers, and founders to ensure infrastructure supports rapid iteration and reliable delivery.
Document infrastructure decisions, runbooks, and operational procedures to support team knowledge sharing and onboarding.
Regularly review and improve operational workflows, automation coverage, and infrastructure cost efficiency.

4+ years of experience in DevOps, SRE, or similar infrastructure-focused roles.
Proficient in AWS with strong Infrastructure-as-Code experience (Terraform preferred).
Strong CI/CD expertise with GitHub Actions.
Experience with containerization and serverless architectures.
Skilled in monitoring, logging, and incident management.
Strong scripting and automation skills in Bash, Python, or Node.js.
Knowledge of cloud security principles, least privilege, and compliance requirements.
Experience with Snowflake and data engineering workflows (ETL, dbt).
Exposure to Kubernetes and orchestration tools.
Understanding of serverless event-driven pipelines (Step Functions, Temporal).
Demonstrated, regular use of AI-powered development tools (e.g., Cursor, GitHub Copilot, Claude Code, or similar) to accelerate infrastructure authoring, debugging, or documentation workflows.
Startup mindset: hands-on, resourceful, and comfortable operating in a fast-paced environment.

Experience with event-driven workflow orchestration tools such as Step Functions, Temporal, Airflow, or Prefect.
Familiarity with agentic workflow patterns, including integrating API-based decision points, asynchronous task handling, and dynamic routing of requests.
Understanding of infrastructure requirements for AI-powered automation, including latency optimization, autoscaling strategies, and cost-efficient compute for high-throughput processes.
Ability to design secure secrets and configuration management systems for agentic processes, including API keys, model tokens, and external service credentials.
Experience implementing observability for multi-step workflows, including distributed tracing, structured logging, and audit-friendly data pipelines.
Experience with prompt engineering for IaC generation, incident analysis, or building AI-powered operational tooling.
Prior early-stage startup experience is highly preferred