Lead AI Platform Engineer
J
JobgetherTechnology
BrazilFull-TimeLead
Salary not disclosed
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Job Details
- Languages
- Advanced English proficiency
- Required Skills
- PythonBashRESTful APIsTerraformGitHub ActionsLLM
Requirements
- 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.
- Advanced English proficiency for technical communication and collaboration with global teams.
Responsibilities
- 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, and AWS Bedrock.
- 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.
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