Lead AI Platform Engineer
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead AI Platform Engineer based in Brazil.
This is a strategic opportunity for an experienced engineer to design and evolve a corporate-scale generative AI platform within a global technology environment.
The role focuses on building secure, scalable, and observable AI infrastructure that enables teams to adopt AI solutions efficiently.
You will work at the intersection of cloud architecture, platform engineering, automation, security, and artificial intelligence.
The position requires strong technical ownership, autonomy, and the ability to translate complex challenges into practical solutions.
You will collaborate with international teams and contribute to enterprise AI initiatives using leading cloud and AI technologies.
This role is ideal for someone passionate about modern engineering practices, governance, and building platforms that drive innovation at scale.
Accountabilities:
The Lead AI Platform Engineer will be responsible for designing, implementing, and continuously improving a centralized AI platform that supports secure and scalable adoption of generative AI solutions. The role combines hands-on engineering with architectural leadership, requiring strong collaboration across technical teams and stakeholders.
- Design, build, and operate a corporate AI Gateway using Azure API Management (APIM).
- Develop governance, authentication, routing, security, and observability strategies for generative AI workloads.
- Integrate multiple AI providers and platforms, including Azure OpenAI, Azure AI Foundry, GCP Vertex AI, AWS Bedrock, and other AI services.
- Implement FinOps practices for AI workloads, including quota management, token budgeting, cost tracking, and usage optimization.
- Develop and maintain infrastructure as code solutions using Terraform or OpenTofu.
- Build and evolve CI/CD pipelines with GitHub Actions, including secure authentication using OIDC.
- Create centralized monitoring and observability solutions using tools such as Application Insights, KQL, Datadog, CloudWatch, and dashboards.
- Develop API management policies for streaming, transformations, retries, fallback strategies, and backend routing.
- Strengthen platform security through identity management, JWT validation, WAF configuration, Key Vault, and secure access patterns.
- Automate operational workflows using scripting languages such as Python, Bash, and PowerShell.
- Produce technical documentation, OpenAPI specifications, and communication materials for technical and business audiences.
- Support internal teams in adopting generative AI solutions safely and efficiently.
- Provide technical guidance, prioritize improvements, and contribute to the continuous evolution of the platform.
- Solid experience with Azure API Management (APIM) and cloud-based platform engineering.
- Strong understanding of Large Language Models (LLMs), including tokenization, context windows, reasoning models, and multimodal AI workloads.
- Hands-on experience with Azure OpenAI and Azure AI Foundry.
- Experience designing and integrating multi-cloud architectures involving different AI providers.
- Strong knowledge of Infrastructure as Code practices using Terraform or OpenTofu.
- Experience building CI/CD pipelines with GitHub Actions and secure authentication using OIDC.
- Advanced understanding of REST APIs, OpenAPI 3.x, SSE streaming, and request/response transformations.
- Experience with observability solutions such as Application Insights, KQL, Datadog, CloudWatch, or similar platforms.
- Knowledge of AI workload governance, rate limiting, quotas, and FinOps strategies.
- Experience with authentication and authorization technologies including Azure AD, OAuth2/OIDC, and JWT validation.
- Strong troubleshooting and problem-solving skills in distributed environments.
- Experience with automation using Python, Bash, or PowerShell.
- Advanced English proficiency for technical communication and collaboration with global teams.
- Degree or equivalent professional experience in Computer Science, Engineering, Information Technology, or related fields.
- Experience with GCP Vertex AI and AWS Bedrock.
- Familiarity with Adobe Firefly APIs or multimodal AI platforms.
- Experience with Kubernetes and containerized environments.
- Knowledge of cloud cost governance, chargeback, and showback models.
- Advanced experience with WAF tuning and Azure Front Door.
- Experience building internal developer platforms (IDPs).
- Familiarity with Azure Terraform providers and advanced infrastructure automation.
- Experience creating self-service observability dashboards.
- Relevant certifications in Azure, Kubernetes, FinOps, or cloud technologies.
- Previous experience working in global enterprise environments.
- Fully remote or hybrid work model, providing flexibility to work from different locations.
- All necessary equipment for your work, including notebook and peripherals.
- Health and dental insurance.
- Life insurance coverage.
- Mental health support program.
- Meal and food allowance through a flexible benefits card.
- Home office assistance.
- Mobility allowance.
- Flexible working hours within a 40-hour work week.
- Birthday day off.
- Access to mentoring programs focused on career development.
- Participation in development tracks, training programs, and online learning platforms.
- Private English classes with instructors.
- Wellness benefits, including access to fitness programs.
- Recognition program with opportunities to give and receive rewards.
- Exclusive themed gifts and internal engagement initiatives.
- Opportunity to work with multicultural teams on global technology projects.
- Collaborative environment focused on innovation, learning, and continuous growth.
Requirements:
The ideal candidate is a highly experienced software engineer with strong expertise in cloud platforms, AI infrastructure, automation, and enterprise-grade application development. You should be comfortable leading complex technical initiatives, solving distributed systems challenges, and collaborating with international teams.
Nice to have:
Benefits:
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1