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 role offers the opportunity to lead the engineering of a large-scale generative AI platform designed for enterprise environments.
You will architect, build, and operate AI infrastructure that enables secure, scalable, and governed adoption of artificial intelligence.
The position combines cloud engineering, platform development, automation, and AI expertise across multiple technology ecosystems.
You will work with cutting-edge AI services and collaborate with global teams to create reliable solutions for complex business needs.
Your contributions will directly impact how organizations consume, govern, and scale AI workloads across enterprise environments.
This is an opportunity for a senior technology professional to shape the future of AI platforms through innovation, automation, and cloud-native engineering.
Accountabilities:
- Design, build, and operate a centralized enterprise AI Gateway using Azure API Management (APIM) to support scalable generative AI workloads.
- Develop advanced governance, authentication, routing, security, and observability policies for AI-powered applications.
- Integrate multiple AI providers and platforms, including Azure OpenAI, Azure AI Foundry, GCP Vertex AI, AWS Bedrock, and multimodal AI services.
- Implement FinOps strategies for AI workloads, including consumption monitoring, quota management, token budgeting, and cost attribution.
- Build and maintain infrastructure as code solutions using Terraform/OpenTofu to enable reliable and repeatable deployments.
- Develop and improve CI/CD pipelines with GitHub Actions, including secure authentication flows using OIDC.
- Create centralized observability solutions using tools such as Application Insights, KQL, Azure Workbooks, Datadog, and CloudWatch.
- Design and maintain API management policies involving streaming, request/response transformation, retries, fallback mechanisms, and backend routing.
- Strengthen platform security through identity management, JWT validation, WAF configuration, Front Door, and Key Vault integrations.
- Automate operational processes using scripting languages such as Bash, Python, and PowerShell.
- Create technical documentation, OpenAPI specifications, and communication materials for both technical and non-technical stakeholders.
- Support internal teams in adopting generative AI solutions securely and efficiently.
- Translate complex technical decisions into clear recommendations for different audiences.
- Work autonomously to identify improvements, prioritize initiatives, and continuously evolve the AI platform.
Requirements:
- Extensive experience with Azure API Management (APIM) and enterprise-scale API platforms.
- 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 implementing multi-cloud architectures and integrations between AI service providers.
- Solid knowledge of Terraform/OpenTofu and infrastructure as code practices.
- Experience building CI/CD pipelines with GitHub Actions, including OIDC-based authentication without stored secrets.
- Strong understanding of REST APIs, OpenAPI 3.x specifications, SSE streaming, and request/response transformations.
- Experience with observability solutions such as Application Insights, KQL, Datadog, CloudWatch, or similar platforms.
- Knowledge of AI cost management strategies, quotas, rate limiting, and FinOps practices.
- Experience implementing authentication and authorization solutions using Azure AD, OAuth2/OIDC, and JWT validation.
- Strong troubleshooting skills and experience analyzing issues in distributed environments.
- Experience automating workflows and operations using Bash, Python, or PowerShell.
- Advanced English proficiency for technical communication and collaboration with international teams.
Nice-to-have qualifications:
- Experience with GCP Vertex AI, AWS Bedrock, or other AI cloud platforms.
- Knowledge of Adobe Firefly APIs or multimodal AI solutions.
- Experience with Kubernetes and containerized environments.
- Experience implementing cloud cost governance, chargeback, or showback models.
- Advanced knowledge of WAF tuning and Azure Front Door.
- Experience building internal developer platforms (IDPs).
- Familiarity with Terraform azapi provider.
- Experience creating advanced observability dashboards and self-service monitoring solutions.
- Relevant certifications in Azure, Kubernetes, or FinOps.
- Experience working in global enterprise environments with complex multi-cloud architectures.
Benefits:
- All necessary equipment provided for remote work, including laptop and peripherals.
- Health and dental insurance.
- Life insurance coverage.
- Mental health support program.
- Flexible work model with anywhere office options.
- Meal and food allowance through benefits card.
- Home office allowance.
- Mobility assistance benefits.
- Career development support through mentoring programs.
- Access to learning tracks, courses, and self-learning platforms.
- Private English lessons with instructors.
- Exclusive gifts and recognition initiatives.
- Gym membership benefits.
- Flexible working hours with a 40-hour workweek.
- Birthday day off.
- Employee recognition program with rewards and appreciation initiatives.
- Fully remote or hybrid work options.
- Opportunity to collaborate with multicultural teams on global technology projects.
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!
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.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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