Antonio Da Fonseca Correia
DevOps & MLOps | AI Platform Engineer
Paris · Annecy · Geneva
AI Platform Engineer — DevOps & MLOps, over five years' experience in startups and scale-ups. Coming from law, self-taught from 2019, now on a permanent contract at Craft AI, working on an AI platform in production. I cover the full chain, down to security and FinOps. French, English, Portuguese. Available in three months.
Antonio Da Fonseca
Coming from law, I moved into tech in 2019 and taught myself: online courses, personal projects, and production environments that had to be brought back up when they went down. I'm now an AI Platform Engineer — DevOps & MLOps, responsible for cloud infrastructure and AI platforms in production.
That path left me with a skill: explaining a technical subject to a management team as clearly as to people who never touch code. I deliver documented, transferable work — what I build can be picked up without depending on me. I also watch what an infrastructure costs, not just what it does: cloud waste is rarely visible before the invoice. I've worked with teams in Paris, the USA and remotely, in French, English and Portuguese.
I'm now seeking to map that path out for others: I'm building BIT — Break Into Tech, a programme for non-technical professionals and people changing careers, aimed at the roles that are genuinely under-filled rather than the most crowded ones. It's the same standard I apply on assignments: what hasn't been handed over isn't finished.
Career path
Measurable results, real teams.
On a permanent contract for a production AI platform, I own the full lifecycle of developing, deploying and monitoring ML and LLM models.
- IaC architecture overhaul: migration and consolidation of 30+ Terraform modules into a modular v2 multi-provider structure — less duplication, faster onboarding onto new environments.
- Multi-cloud infrastructure management (AWS, GCP, Scaleway) across 50+ client environments: harmonized naming conventions, variables and outputs across the 3 providers for consistency and maintainability at scale.
- Full AI/ML monitoring stack: Prometheus (infra metrics), Grafana (real-time dashboards), OpenObserve (log aggregation).
- Cloud cost optimization: full AWS audit, Reserved Instances, EC2/RDS rightsizing — 10% lower monthly spend.
- Close collaboration with Data Science teams: model productionization, inference latency optimization, ML pipeline improvements.
- Automated ML model deployment via GitHub Actions and Jenkins: full CI/CD with automated tests, model validation and progressive rollout.
- MLOps architecture documentation: infrastructure diagrams, operational runbooks and troubleshooting guides.
On a DevOps engineer mission for a premium sneakers e-commerce platform: AWS cloud infrastructure and DevOps automation.
- Incident diagnosis & resolution: analysis and resolution of production and development incidents (application errors, deployment issues, performance degradation) using New Relic and AWS CloudWatch.
- Automated provisioning (IaC): development environments, ECS services and EC2 instances automated with Terraform.
- AWS IAM administration: managing accounts, groups, roles, access policies and permissions following the principle of least privilege.
- Bash automation scripts: recurring operations — database backups and restores, production database access control.
- MySQL administration: users, databases, tables, access rights and application privileges.
- CI/CD with GitHub Actions & Docker: creating and maintaining Dockerfiles and GitHub Actions workflows for continuous integration and deployment.
- CI/CD pipeline optimization: deployment reliability, faster delivery and environment stability.
- DevOps ↔ Slack integration: streamlined approvals, centralized New Relic alerts, error-rate tracking and platform health monitoring.
- AWS Lambda functions (Python): automating and optimizing operational workflows.
- DevOps documentation on Notion: operating procedures, infrastructure diagrams, database access, monitoring tutorials and internal processes.
Linux systems administration and DevOps automation for a distributed multi-server infrastructure.
- Linux systems administration: user accounts and permissions via CLI, system performance monitoring (CPU, RAM, disk), log analysis for troubleshooting.
- Maintenance automation: Bash scripts for automatic system updates and security patches, cutting maintenance time.
- Advanced Bash scripting: automation of admin tasks (log rotation, cron jobs, incremental backups) and server health monitoring with alerting.
- Web server configuration: Apache and Nginx setup and tuning (static and dynamic sites), SSL/TLS configuration, load balancing.
- Network security: firewall rules (iptables, security groups), SSH hardening, certificate management.
- Secure remote access: key-based SSH authentication, authorized_keys management, bastion hosts.
- Virtual machine deployment: creating and managing VMs with VirtualBox and VMware for dev/test environments, reusable templates.
- Backup / recovery strategies: automated backup solutions, regular restore testing, documented disaster recovery procedures.
- Technical documentation: system configuration guides, troubleshooting procedures, architecture documentation for the team.
Technologies I master
Ten families, from provisioning to observability.
Click the central node to expand the map.
Let's work together
Open to freelance assignments and permanent roles. Hybrid from Paris or Annecy, on site in Geneva.