Senior Dev Ops Engineer

Sermo; Brasil; On-site; BRL 180,000 - 270,000; Full time

Job summary

SERMO is seeking a skilled DevOps engineer to join our team and ensure our infrastructure runs smoothly, with a focus on AI-assisted development. You will work across Engineering and IT, shaping tool usage, pipelines, and runbooks, while maintaining production safety and cost controls.

You will direct AI agents, review outputs, and own the final results. Collaboration, ownership, and a systematic approach to problem-solving are essential in this fast-paced environment.

Qualifications

• 4+ years in a similar DevOps role.
• 4+ years of Linux system administration.
• Good understanding of Windows system administration.
• Extensive experience with AWS.
• Strong knowledge of Docker/Kubernetes/AWS ECS infrastructure.
• Experience with Datadog monitoring.
• Experience with IaC (Terraform/OpenTofu/Terragrunt).
• Experience with CI/CD pipelines (GitLab).
• Scripting in Python, Bash, or PowerShell.
• Strong English communication (C2).
• On-call availability in rotation.

Responsibilities

• Implement improvements to the automated DevOps framework using AI agents.
• Maintain build environments across platforms.
• Collaborate to upgrade OS and migrate to Docker containers.
• Monitor production in AWS and Datadog.
• Participate in pager duty for system stability.
• Troubleshoot production issues leveraging AI-assisted analysis.
• Review infrastructure changes for security and blast radius.
• Assist backup/restoration processes.
• Review AI-generated MR changes for correctness and security.
• Improve agent instructions and tooling for reliable AI-assisted work.
• Guide teams in adopting AI tooling safely.

Skills

Linux admin

AWS

Docker/Kubernetes

CI/CD

Python/Bash

Git

AI tooling

English (C2)

On-call

Tools

Docker

Kubernetes

AWS

Datadog

Terraform/OpenTofu/Terragrunt

Packer

CloudFormation

Ansible

GitLab

Job description

SERMO® is the world’s largest social network for physicians and a global leader in healthcare data collection. We have over 16 years of experience in healthcare fieldwork and a network of 2 million medical professionals worldwide, as well as the number one social network for doctors. Our mission is to revolutionize real-world medicine by connecting doctors around the world to the wisdom and support of their peers.

SERMO is an international company with over 500 employees across eight countries. We are a culturally diverse group of individuals with backgrounds in technology, product, social networks, market research, healthcare, and international business. As a performance driven, dynamic company, our aim is to provide the best customer experience possible, while actively encouraging and supporting each employee’s continued growth and development.

SERMO is an Equal Opportunity Employer.

Summary

We are looking for a very skilled Dev Ops engineer who uses AI tools every day. You will join the Dev Ops team and work alongside the existing teams (Engineering and IT) to make sure our infrastructure continues to run smoothly. You will have a lot of flexibility in terms of the technologies you use daily, and you will have a say in how those technologies should be used going forward.

Much of Dev Ops work suits AI-assisted development: infrastructure as code, pipelines, scripts, runbooks, and the first pass of troubleshooting. We expect you to use AI tools such as Claude Code or equivalent to deliver it quickly while keeping production safe. You will direct AI agents, review what they produce, and own the result. Infrastructure changes can affect every product we run, so judgement about when to trust the tool, and when not to, matters as much as speed.

We expect you to be a team player and enjoy collaborating with others to find the best solution to a problem, and comfortable working in a dynamic work environment where change is expected. You have a service-oriented mindset and like to take ownership and follow your tasks through to completion. You should also have a systematic and logical approach to solving problems and enjoy teaching and mentoring other coworkers with your knowledge and new findings, including the AI practices that work.

How we use AI in Dev Ops

• We use AI tools such as Claude Code or equivalent to plan, write, test, review, and document infrastructure code, pipelines, scripts, and runbooks.

• Your job is to write clear specifications, direct the agents, and verify the result before it reaches production: read the plan or diff, test in a non-production environment first, and check security and cost impact.

• We invest in the instructions, tools, and guardrails that make AI-assisted work reliable and safe, such as least-privilege credentials for agents, read-only access to production by default, CI checks, and shared instruction files. Dev Ops engineers help build them.

• Sensitive data, credentials, and secrets are handled under our data-protection rules. You keep them out of prompts and logs, and you raise data-handling risks early.

• Every change gets human review, whoever or whatever wrote it, and you own what you ship.

Day to day tasks:

• Implement improvements to our automated Dev Ops framework (release scripts, tools, build environments, etc.), using AI agents to speed up writing, refactoring, and testing infrastructure code, pipelines, and scripts.

• Improve and maintain build environments across multiple platforms.

• Collaborate with developers on ways to continuously improve infrastructure, such as upgrading operating systems and migrating to Docker containers.

• Monitor production environments in AWS and in Datadog.

• Participate in the pager duty and call rotation to ensure system stability.

• Detect, troubleshoot, and help resolve production issues. Use AI assistance to correlate logs, metrics, traces, and recent changes and to speed up triage, and verify its conclusions before acting on production.

• Help ensure that our systems meet general security standards, including reviewing infrastructure changes (AI-generated or not) for IAM scope, exposed resources, and secrets handling.

• Facilitate backup and restoration of our systems.

• Review merge requests, including AI-generated changes, for correctness, security, blast radius, and maintainability.

• Improve the instructions and tooling our agents rely on (for example CLAUDE.md files, scripts, MCP servers, permission settings, and CI checks) so AI-assisted work is reliable for the whole team, and define how agents may access AWS and production.

• Use AI to reduce toil and keep documentation current: runbooks, incident timelines, post-incident reviews, and onboarding material.

• Help engineering teams adopt AI tooling safely, including environments, access, and secrets handling, and share the prompts and practices that work.

• Help decide which technologies and processes we use.

Minimum requirements:

• 4+ years of experience in a similar dev ops role

• 4+ years of Linux system administration

• Good understanding of Windows system administration

• Extensive experience with AWS.

• Clear understanding of the AWS well architected framework, AWS Organizations, AWS Identity Center, IdP configurations and multi-account segregation.

• Extensive experience with Docker/Kubernetes/AWS ECS container infrastructure and orchestration

• Must have good experience with DataDog

• Extensive experience in Infrastructure as Code such as Terraform/OpenTofu/Terragrunt

• Also have experience with at least: Packer, CloudFormation or Ansible experience

• Extensive experience building CI/CD pipelines, preferably in Gitlab.com

• Knowledge and experience with scripting tools and languages, such as Python, Bash and Powershell.

• Advanced experience with Git version control system, including branching strategies, MRs and downstream pipelines.

• Hands-on experience using AI coding tools such as Claude Code or equivalent for infrastructure, pipeline, or operations work, at work or on your own projects. Be ready to walk us through what you shipped, how you checked it, and where you overruled the tool.

• Ability to verify AI-generated infrastructure changes: reading plans and diffs, testing in non-production environments, and checking them against security, reliability, and cost.

• Understanding of the risks of giving AI agents access to cloud accounts and production systems, and of the controls that contain them (least privilege, scoped credentials, secrets handling, audit trails).

• Excellent English written and verbal communication skills, with a C2 proficiency level. Clear writing matters more when specifications drive the work.

• Availability for being on-call during off‑hours and weekends in a rotation with other engineers for pager duty.

Bonus skills and experience:

• Experience configuring AI coding agents (for example CLAUDE.md files, skills, hooks, or MCP servers) or running several agents in parallel

• Experience with AI guardrails technologies such as AWS Bedrock

• Experience provisioning and configuring environments in Databricks

• Experience connecting AI tools to operational systems such as Datadog, AWS, GitLab, and Jira (for example through MCP servers), and using them for log analysis and incident triage

• Experience with policy as code and automated guardrails for infrastructure (for example OPA, Checkov, or tfsec)

• Experience building internal automation with LLM APIs, AWS agentcore and development of autonomous AI agents.

• Experience implementing controls related to SOC 2 / HIPAA or other compliance framework

• Understanding of GDPR and data-protection requirements when using AI tools with sensitive data

• Understanding of the AWS tenant concept and architecture

• Experience with PostgreSQL

• Experience building CI/CD pipelines for .NET Core (C#) projects

• Experience with other SQL servers and technologies such as Redshift

• Experience with Solr

• Experience using JIRA

• Understanding of network technologies as they relate to AWS, such as Transit Gateways, site-to-site VPNs, VPC routing and Zero Trust Network Access solutions such as Tailscale / Twingate. Monitoring and auditing systems experience

• Understanding and experience with the medical industry

• An ability to perform well in a fast‑paced environmen