Senior AI Systems Architect — Hybrid, Enterprise-Scale

Goliath Partners Inc.; San Francisco (CA); Hybrid; USD 270,000 - 325,000; Full time

Job summary

Goliath Partners Inc. in San Francisco is seeking a Senior AI Engineer to drive the core systems that power its next generation of intelligent software.

You will own architectural decisions, shape the platform, and build reliable AI-enabled infrastructure at scale. Joining a lean, highly skilled team, you will integrate external tools, manage complex workflows, and ensure production readiness with observability and robust validation.

Qualifications

• Extensive experience across AI platforms, backend infra, ML systems, or distributed computing.
• Proven production software delivery involving large language models or AI agents.
• Knowledge of LLM ecosystems: model-serving APIs, function calling, retrieval augmented generation.
• Ability to evaluate frameworks and technologies for performance and reliability.

Responsibilities

• Architect and develop core infrastructure enabling AI-powered apps to interact with APIs and manage state.
• Build execution frameworks for LLM requests, tool usage, API integrations, and workflows.
• Develop scheduling, persistence, execution control, and decision management for AI apps.
• Design modular interfaces for integration with foundation models and inference platforms.
• Establish evaluation pipelines to measure model behavior and improve quality.
• Implement observability with tracing, logging, metrics, and monitoring for reliability.

Skills

AI platforms

Backend infra

Machine learning systems

Distributed computing

Education

Bachelor's or advanced degree in Computer Science/Engineering or related

Job description

Goliath Partners Inc. in San Francisco is seeking a Senior AI Engineer to drive the core systems that power its next generation of intelligent software.

You will own architectural decisions, shape the platform, and build reliable AI-enabled infrastructure at scale. Joining a lean, highly skilled team, you will integrate external tools, manage complex workflows, and ensure production readiness with observability and robust validation.