Senior AI Engineer

Goliath Partners; San Francisco (CA); On-site; USD 245,000 - 300,000; Full time

Job summary

Goliath Partners in San Francisco is seeking a Senior AI Engineer to define and build the infrastructure powering its next wave of AI products. You will work at the intersection of AI infrastructure, LLM systems, agent architecture, orchestration, and distributed production systems.

You'll collaborate with senior engineering leadership to turn early prototypes into robust production platforms, shaping technical direction and enabling scalable AI capabilities across the business.

Qualifications

• Bachelor's, Master's, or PhD in CS/EE or related field preferred.
• Experience deploying AI-driven products and LLM apps.
• Deep familiarity with LLM architectures, APIs, and tool calling.
• Ability moving between exploratory development and production systems.
• Strong software and systems engineering fundamentals.

Responsibilities

• Architect and implement foundational AI services and runtimes.
• Engineer AI agent orchestration and multi-stage workflows.
• Design model-agnostic infrastructure for multiple foundation models.
• Establish production observability for AI workloads.
• Lead end-to-end from exploration to deployment in production.

Skills

Software engineering

AI products

LLM architecture

AI environments

Technical instincts

Software fundamentals

Dev to Prod

Ownership

Greenfield

Leadership

Education

BS/MS/PhD in CS/EE

Job description

We’re partnering with an emerging AI company developing intelligent systems that allow enterprise teams to automate sophisticated, high-impact processes. As the company expands its platform, the engineering organization is building the technical foundation required to make AI-driven applications dependable, scalable, and increasingly autonomous in real-world environments.

The team is hiring a Senior AI Engineer to help define and build the infrastructure powering its next wave of AI products. This is a highly hands-on, greenfield position sitting at the intersection of AI infrastructure, LLM systems, agent architecture, orchestration, retrieval, evaluation, and distributed production systems.

You’ll operate closely with senior engineering leadership and have significant influence over technical direction. The ideal candidate is equally comfortable exploring an emerging AI capability, designing the underlying architecture, and turning an early prototype into a robust production system.

What You’ll Build

• Architect and implement foundational services for AI-powered applications, including agent runtimes, execution environments, state and memory systems, tool use, external integrations, and computer-interaction capabilities.
• Engineer the infrastructure that enables AI agents to break down objectives, reason over context, select appropriate actions, and execute multi-stage workflows.
• Build orchestration systems that dynamically manage models, tools, APIs, and execution paths according to the needs and constraints of individual workloads.
• Design model-agnostic infrastructure that can integrate multiple foundation models, inference providers, APIs, and emerging AI technologies.
• Establish production observability across AI workloads, measuring factors such as latency, reliability, cost, agent behavior, task completion, and system performance.
• Develop the evaluation layer for AI applications, including test suites, benchmarks, datasets, automated scoring, and other mechanisms for measuring model and workflow quality.
• Investigate developments across LLMs, retrieval systems, agent frameworks, model tooling, and computer-use technologies and translate relevant advances into usable platform capabilities.
• Rapidly prototype new approaches involving prompting, retrieval, model selection, fine-tuning, agent architecture, and workflow execution.
• Lead initiatives from early technical exploration through deployment, hardening, scaling, and ongoing operation in production.
• Partner with engineering leadership on platform architecture, technical tradeoffs, and prioritization as the AI stack evolves.
• Establish reusable system abstractions, engineering patterns, and technical standards that support long-term scalability and maintainability.

What You’ll Bring

• Strong foundation in software engineering, computer science, distributed systems, AI engineering, or a related technical discipline. A Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or a comparable field is preferred.
• Demonstrated experience developing and deploying AI-driven products, LLM applications, agent platforms, intelligent automation systems, or similarly complex AI technologies.
• Deep familiarity with modern LLM application architecture, including model APIs, function/tool calling, retrieval, prompting, agent frameworks, orchestration, and model routing.
• Experience building in fast-moving AI environments where models, frameworks, infrastructure, and best practices are evolving rapidly.
• Strong technical instincts when evaluating emerging technologies, with the ability to distinguish promising concepts from those that can realistically be productionized.
• Excellent software and systems engineering fundamentals, particularly when working through ambiguous or technically complex problems.
• Experience moving between exploratory development and production engineering without losing sight of reliability, scalability, and maintainability.
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• A high degree of ownership and autonomy, with the judgment to drive projects independently and contribute to architecture-level technical decisions.
• Enthusiasm for greenfield systems work and the opportunity to help establish the engineering foundation of a rapidly evolving AI platform.

Compensation & Location

• Base Salary: $245,000 – $300,000, depending on experience
• Opportunity: Work closely with senior technical leadership while shaping the infrastructure, architecture, and systems that underpin the company’s core AI capabilities as the platform scales.