Lead AI Platform Engineer

Role Overview

• Design, build, and operate the corporate AI Gateway using Azure API Management (APIM).
• Develop advanced governance, authentication, routing, and observability policies for generative AI workloads.
• Integrate multiple AI providers, including Azure OpenAI, Azure AI Foundry, GCP Vertex AI, AWS Bedrock, and Adobe Firefly.
• Implement FinOps mechanisms to control consumption, per-subscription quotas, token budgeting, and cost attribution.
• Develop and maintain infrastructure as code (IaC) using Terraform/OpenTofu.
• Build and evolve CI/CD pipelines with GitHub Actions using OIDC authentication.
• Create centralized observability mechanisms using Application Insights, KQL, Azure Workbooks, Datadog, and CloudWatch.
• Develop APIM policies for SSE streaming, request/response transformation, retry, fallback, and backend routing.
• Work on platform security using Azure AD, JWT validation, WAF tuning, Front Door, and Key Vault.
• Automate operations and administrative workflows using Bash, PowerShell, and Python.
• Produce technical documentation, OpenAPI specs, and materials for technical and non-technical stakeholders.
• Support internal teams in the secure and scalable adoption of generative AI.
• Translate technical limitations and architectural decisions into clear recommendations for different audiences.
• Work autonomously to identify needs, prioritize improvements, and continuously evolve the platform.

Requirements

• Strong experience with Azure API Management (APIM).
• Deep understanding of Large Language Models (LLMs), including tokenization, context windows, reasoning models, and multimodal workloads.
• Experience with Azure OpenAI and Azure AI Foundry.
• Experience with multi-cloud architectures and integrations between AI providers.
• Experience with Terraform/OpenTofu and infrastructure as code.
• Experience with GitHub Actions using OIDC (without persisted secrets).
• Knowledge of REST APIs, OpenAPI 3.x, SSE streaming, and request/response transformation.
• Experience with observability using Application Insights, KQL, Datadog, or similar tools.
• Knowledge of quota control, rate limiting, and FinOps strategies applied to generative AI.
• Experience with authentication/authorization using Azure AD, OAuth2/OIDC, and JWT validation.
• Knowledge of troubleshooting and problem analysis in distributed environments.
• Experience with automation using Bash, Python, or PowerShell.
• Advanced English for technical communication and international collaboration.

Tech Stack

• AWS
• Azure
• Cloud
• Google Cloud Platform
• Python
• Terraform
• Vault

Benefits

• All necessary equipment for your work (laptop and peripherals);
• Health and dental insurance;
• Life insurance;
• Mental health program;
• Anywhere office – flexibility to work from wherever you need;
• Meal and food allowances (VR/VA) (Flash benefits card);
• Home office allowance (Flash benefits card);
• Mobility allowance (Flash benefits card);
• Mentorship program for career development and guidance;
• Access to development tracks (investment in courses, etc.) and to our free learning platform with many self-learning courses;
• Private English lessons with a personal instructor;
• Awesomeness – delivery of themed and exclusive gifts;
• Gympass;
• Flexible working hours (40 hours per week);
• Birthday day off;
• Appreciation – recognition program with the option to give and receive monthly 'dentsu dollars';
• Fully remote or hybrid work (your choice).