Description
GlobalLogic estimates the starting base salary for the Python Full stack AI Engineer position in Minneapolis, MN to be between $160000 to $180000 and reflects base salary only and does not include additional performance-linked variable compensation, benefits etc that may be applicable for the role. This pay range is provided as a good faith estimate and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.
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.
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.
Build 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.
Develop configuration frameworks such as runtime settings, execution modes, feature flags, and environment-specific parameters.
Validate and improve game/test harness usability, reliability, and developer experience.
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.
Ensure all source code, tests, documentation, and configuration comply with client -defined coding standards, testing requirements, security policies, and review processes.
