01
Role requirement
Cloud platforms
Scalable AWS architecture, Kubernetes / EKS, containerized workloads, and infrastructure as code.
Open to DevOps conversations
AWS infrastructure · automation · reliability
I turn cloud challengesinto reliable,repeatable solutions.
I help teams improve AWS operations with Python automation, containerized solutions, monitoring, cost awareness, and secure cloud connectivity.
Current roleDevOps Engineer · Infosys Consulting
Engineering focusAWS · Python · Docker · Cloud operations
Based inSão Paulo, Brazil · Distributed teams
AWSAWSK8SKubernetesCICI/CDGITGitOpsTFTerraformPYPythonDKDockerLNXLinuxMONCloud MonitoringNETCloud NetworkingFINCost Optimization
AWS
Solutions ArchitectAssociate certified
LPI
LPIC-1Certified Linux Administrator
PROJ
Cloud deliveryAutomation, access, monitoring, and cost
TEAM
Collaborative deliveryClear planning for challenging solutions
AWS architecture study
Secure document delivery, designed in layers.
A reference architecture showing how I reason about identity, private connectivity, serverless orchestration, data lifecycle, encryption, and operational visibility on AWS.
Reference architecture · design study
Client / browserUploads and restore requests
AWSAWS CloudRegion · sa-east-1
Security edgeValidate identity and protect the API
AWS WAF
AWS Shield
Amazon Cognito
Amazon API GatewayREST · WebSocket · Cognito authorizer
Private VPCPrivate compute zone
AWS LambdaUpload · query · restore orchestration
VPC endpoints
S3 endpoint
DynamoDB endpoint
Private paths to S3 and DynamoDBManaged data services
Amazon S3 StandardEncrypted object storage · versioning
S3 Glacier Flexible RetrievalLifecycle archival · 6–12h retrieval
Amazon DynamoDBDocument metadata and status index
Amazon SNSRestore completion notification
Governance & observability
Amazon CloudWatch
AWS CloudTrail
AWS KMS
AWS IAM
Architecture flow
- 01WAF, Shield, and Cognito protect and validate entry.
- 02API Gateway invokes Lambda inside the private compute boundary.
- 03Lambda issues a presigned URL through an S3 VPC endpoint.
- 04DynamoDB tracks document metadata and restoration state.
- 05S3 Lifecycle transitions objects to Glacier for long-term retention.
- 06SNS notifies the client when a restoration completes.
Conceptual reference design created to demonstrate architecture reasoning. It is not presented as a deployed client system.
Recruiter alignment
The outcomes modern DevOps roles keep asking for.
The opportunities reaching me consistently converge on scalable cloud platforms, dependable delivery, strong observability, and confident production ownership.
Recurring role briefAWS · Kubernetes / EKS · Terraform · CI/CD · Observability · Python · Production support
This section mirrors recurring recruiter requirements. Verified project work and credentials are separated below for a transparent view of experience and direction.
02
Role requirement
Delivery automation
Repeatable CI/CD, deployment safeguards, environment consistency, and Python infrastructure tooling.
03
Role requirement
Reliability & visibility
Production support, alerting, application health, cost signals, and observable cloud operations.
04
Role requirement
MLOps workloads
Workload orchestration and platform foundations for training, evaluation, deployment, and model health.
Verified project experience
Engineering shaped for reliability and clarity.
Selected solutions delivered in client environments, framed around the engineering problem, approach, and outcome without exposing confidential infrastructure.
Governed LLM access with Kong AI Gateway and Amazon Bedrock
Implemented a cloud-native AI platform in which Amazon Bedrock served as the managed access layer for foundation models, Kong AI Gateway centralized and routed inference requests, and Kong's data plane ran on Amazon EKS.
The client gained a unified, governed entry point for LLM services, scalable request routing on Kubernetes, and a more consistent operating model—accelerating the adoption of new AI use cases without fragmented point-to-point integrations.
OutcomeGoverned access + faster AI adoption
Amazon DocumentDB Auto Scaling with Python
Contributed to planning an Auto Scaling solution for Amazon DocumentDB and developed part of the application in Python.
Collaborated on the tool design and automation implementation with the project team.
OutcomePython automation
Containerized client-to-site VPN for AWS
Built a Docker-based client-to-site VPN so developers could access AWS resources and services through secure communication.
The solution enabled cloud access for the team and delivered financial benefits to the project.
OutcomeSecure access + financial benefit
Infrastructure cost monitoring
Implemented a monitoring system to support solutions focused on reducing infrastructure costs.
The system provided a foundation for cost-reduction initiatives within the project.
OutcomeMonitoring + optimization
Capability map
Proof, foundations, and the next platform challenge.
A transparent view of delivered work, the credentials behind it, and the platform and MLOps responsibilities I am positioning for.
01Verified
Project delivery
- AWS cloud infrastructure
- Python automation
- Docker solutions
- Secure cloud networking
- Monitoring-led operations
- Cost optimization
- Solution planning
02Foundations
Certifications & training
- AWS cloud architecture
- Linux administration
- Azure fundamentals
- OCI foundations
- Cloud fundamentals
- Infrastructure foundations
03Target roles
Platform engineering
- AWS / Kubernetes platforms
- Terraform infrastructure
- GitHub Actions CI/CD
- Modern observability
- Deployment consistency
- Technical documentation
04Recurring requirements
MLOps opportunities
- Slurm orchestration
- Model delivery pipelines
- Snowflake Cortex
- Langfuse
- Model health signals
- Distributed collaboration
How I operate
Good platforms make the safe path the fast path.
- 01Stability before release
Surface deployment risk and environment drift before they become production incidents.
- 02Cost is an architecture signal
Connect allocation, utilization, and ownership so optimization becomes part of platform work.
- 03Observability is built in
Treat application, infrastructure, and model health as first-class delivery requirements.
- 04Documentation is infrastructure
Keep security, deployment, and operating workflows clear enough for distributed teams to execute.
Verified credentials
Foundations that support the work.
Cloud and Linux certifications complement practical project experience and continuous learning.
AWS Certified Solutions Architect – Associate
Amazon Web Services
Valid through November 2026Linux Professional Institute LPIC-1
Linux Professional Institute
Valid through November 2027Microsoft Certified: Azure Fundamentals
Microsoft
Cloud fundamentalsOracle Cloud Infrastructure Foundations
Oracle
Cloud infrastructure foundations“Guilherme is dedicated, proactive, and fully engaged in challenging work. His commitment makes his deliveries effective.”
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Looking for a DevOps Engineer for cloud infrastructure challenges?
I am open to DevOps, cloud platform, and MLOps engineering conversations with teams that value reliable delivery, technical depth, and clear ownership.