AI Platform Engineer – Nairobi

About the role

The AI Platform Engineer will administer enterprise AI platforms, manage user access and API configurations, and monitor system performance. The role includes troubleshooting data‑flow issues, supporting AI security and compliance, and maintaining technical documentation and procedures.

Key responsibilities

• Serve as primary technical administrator for IRC AI environments (Anthropic, OpenAI, etc.), handling user access, API key governance, and workspace configurations.
• Monitor system health, usage patterns, token consumption and resolve operational issues across AI tools.
• Develop lightweight scripts, connectors and automations in Python or JavaScript/TypeScript to support AI‑assisted workflows.
• Collaborate with DevOps, software and data engineering teams on integration deployments, change management and environment dependencies.
• Track AI resource utilization, identify cost‑saving opportunities and act as liaison with the InfoSec team on security, data handling and compliance.
• Provide technical support to program and operations teams adopting AI tools, including rollout planning and documentation.

Required profile

• Hands‑on experience administering enterprise AI platforms (Anthropic, OpenAI, Azure OpenAI or similar) and managing API access controls.
• Familiarity with LLM infrastructure, prompt pipelines, vector databases and retrieval‑augmented generation patterns.
• Proficiency in Python and/or JavaScript/TypeScript for scripting and integration work.
• Experience building and maintaining REST API integrations, including authentication and webhook handling.
• Background in monitoring distributed SaaS platforms, setting alerts and diagnosing performance issues.
• Working knowledge of information‑security principles for SaaS and API‑based systems.
• Strong communication skills and ability to produce clear technical documentation.

Required skills

• Python
• JavaScript / TypeScript
• REST API development
• Git version control
• Anthropic platform
• OpenAI platform
• Azure OpenAI
• Databricks or comparable ML/data platform
• Cloud platforms (AWS, Azure, GCP)
• Vector databases and RAG workflows
• Monitoring and usage‑cost tracking tools