Senior AI Engineer

Goliath Partners Inc.; San Francisco (CA); On-site; USD 290,000 - 350,000; Full time

Job summary

Goliath Partners Inc. in San Francisco is seeking an AI Engineer to architect and build the core platform that powers its AI product ecosystem. You’ll own subsystem design across AI infrastructure, orchestration, and backend components.

You’ll translate research into production-ready services, lead scalable architectures, and influence product strategy while collaborating with a small, highly skilled team.

Qualifications

• Strong software engineering fundamentals and experience with AI platforms.
• Production systems experience involving LLMs or AI agents.
• Knowledge of model APIs, function calling, and tool integration.
• Ability to evaluate AI frameworks based on trade-offs for production.
• Backend engineering for high availability, scalability, observability, and performance.
• Translating ambiguous problems into robust architectural solutions with ownership.
• Comfort in early-stage or high-growth environments influencing product decisions.
• Strong communication and collaboration with leadership.

Responsibilities

• Architect and develop foundational platform services for AI-powered apps.
• Build orchestration infrastructure connecting LLMs, APIs, and external systems.
• Develop agent infrastructure for planning, state, decision-making, and execution.
• Design modular components supporting multiple model providers and AI frameworks.
• Implement observability and monitoring for reliability, latency, and costs.
• Establish testing and performance benchmarks for AI-driven apps.
• Evaluate emerging AI tech and translate research into production services.
• Address distributed execution, throughput, latency, fault tolerance, scalability.
• Drive engineering initiatives across architecture to deployment and monitoring.
• Collaborate with leadership to shape platform roadmaps and patterns.

Skills

Backend engineering

Distributed systems

AI platforms / LLMs

Observability

Education

Bachelor’s/Master’s/PhD in Computer Science or Computer Engineering

Job description

We’re partnering with an innovative, fast-growing AI company building intelligent software that enables enterprise organizations to streamline complex operations and automate sophisticated business workflows. As the company transitions from early-stage development to broader enterprise deployment, it is investing in the core infrastructure required to deliver reliable, scalable, and increasingly autonomous AI solutions

The company is looking for a AI Engineer to help architect and develop the systems that power its AI product ecosystem. This role sits at the intersection of AI infrastructure, backend engineering, and distributed systems, with a focus on agent runtimes, orchestration frameworks, enterprise integrations, system evaluation, and production performance.

Working within a small, highly technical engineering team, you’ll have substantial ownership over platform architecture and the opportunity to influence both technical strategy and product evolution. The ideal candidate combines strong systems engineering expertise with a practical understanding of modern AI technologies and a track record of turning experimental capabilities into dependable, production-ready systems.

Key Responsibilities

• Architect and develop the foundational platform services that support AI-powered applications, including execution environments, context handling, tool integrations, and workflow management.
• Build orchestration infrastructure that connects language models, APIs, internal services, and external systems to execute complex, multi-stage business processes.
• Develop agent infrastructure that supports planning, persistent state, decision-making, task execution, and greater operational autonomy.
• Design modular platform components that support multiple model providers, inference approaches, AI frameworks, and emerging architectural patterns.
• Implement observability and monitoring capabilities to measure system reliability, response times, execution outcomes, resource consumption, and infrastructure costs.
• Establish evaluation frameworks, automated testing infrastructure, and performance benchmarks to improve the consistency and quality of AI-driven applications.
• Assess emerging developments in large language models, retrieval-augmented generation, agent architectures, tool use, inference optimization, and computer interaction.
• Convert promising research, proof-of-concepts, and technical experiments into maintainable services suitable for enterprise-scale production.
• Address complex engineering challenges involving distributed execution, throughput, latency, fault tolerance, scalability, and infrastructure utilization.
• Drive technical initiatives across the full engineering lifecycle, from architecture and prototyping to deployment, production monitoring, and ongoing optimization.
• Partner with engineering leadership to shape platform roadmaps, evaluate architectural alternatives, and prioritize investments in foundational technology.
• Create reusable interfaces, development frameworks, and integration patterns that accelerate the delivery of new AI capabilities.
• Help define engineering standards and architectural principles that support long-term platform expansion and increasingly sophisticated AI use cases.

Required Qualifications

• Strong software engineering fundamentals and professional experience in AI platforms, backend infrastructure, distributed systems, machine learning engineering, or a related technical field.
• Demonstrated experience building and operating production systems that incorporate LLMs, intelligent automation, AI agents, or machine learning infrastructure.
• Practical knowledge of modern AI development patterns, including model APIs, structured outputs, function calling, retrieval systems, prompt design, tool integration, and multi-step agent workflows.
• Ability to evaluate AI frameworks, model capabilities, and infrastructure technologies based on their technical trade-offs, operational requirements, and production suitability.
• Deep backend engineering knowledge, with experience designing systems for high availability, scalability, observability, and performance.
• Experience translating ambiguous technical problems into robust architectural solutions and delivering projects with significant engineering ownership.
• Comfort working in an early-stage or high-growth environment where priorities evolve and engineers contribute directly to product and infrastructure decisions.
• Strong communication skills and the ability to collaborate with engineering leadership and cross-functional stakeholders.
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a related discipline preferred.

Compensation & Location

• Base Salary: $290,000–$350,000 annually, depending on experience, qualifications, and scope of responsibility.
• Level: Staff-level individual contributor with substantial architectural ownership and influence over AI platform strategy.