Full Stack Python AI Engineer IRC299254

Job Responsibilities

• Build user-facing workflows for initiating, monitoring, and reviewing game execution runs
• Design and implement backend APIs that expose platform capabilities through stable service contracts
• Build internal tools, CLI capabilities, and developer/user workflows to improve platform usability
• Design and implement run data models, including run manifests, result schemas, metrics structures, logs, outputs, and artifact references
• Build comparison, evaluation, and analytics capabilities to assess performance across runs, configurations, algorithms, environments, and versions
• Implement logging, metrics, diagnostics, and observability capabilities across the execution lifecycle
• Develop UI components for viewing run status, logs, outputs, metrics, comparisons, and generated artifacts
• Implement CRUD-style interactions for logs, results, outputs, artifacts, and execution metadata
• Refactor and improve existing PoC codebase for maintainability, scalability, testability, and production readiness
• Work closely with the Platform Engineer to align APIs, schemas, storage formats, and system integration points
• Work closely with the AI Evaluation & Benchmarking Engineer to support experiment design, metric capture, comparison workflows, and reporting needs

Requirements

• Strong Python application engineering experience
• Experience building internal platforms, developer tools, experimentation systems, dashboards, or data-heavy applications
• Backend API design experience, including service contracts, schemas, boundaries, and integration patterns
• UI development experience using modern web frameworks
• Strong data modeling skills for structured logs, manifests, metrics, results, and analytics outputs
• Experience with observability design, including logs, metrics, diagnostics, and troubleshooting workflows
• Experience with testing, validation, refactoring, and production-quality code practices
• Strong UX thinking for internal tools and developer/user workflows
• Ability to collaborate across platform, infrastructure, data, and AI/ML engineering teams
• Ability to work inside client-owned repositories, infrastructure, workflows, and security controls

Preferred Skills

• Experience with AI/ML evaluation platforms, benchmark systems, experiment tracking, or model performance analytics
• Experience with LLM or reinforcement learning evaluation workflows
• Experience with data visualization, metrics dashboards, or analytics reporting
• Experience with containerized applications and cloud/private infrastructure environments
• Experience with feature flags, runtime configuration, and multi-environment application behaviour
• Experience with artifact management, log exploration, and run comparison interfaces