AI Engineer

AI Engineer

Location:

San Francisco, CA Company Stage of Funding:
Seed Stage AI Startup ($6M Raised) Office Type:
Onsite (5 Days Per Week) Salary: $180,000–$250,000 + Competitive Equity

We're representing a rapidly growing AI infrastructure startup building the intelligence layer that helps enterprise organizations understand how work gets done and where AI can create measurable business impact. Their platform captures workflows across enterprise systems, transforms massive volumes of operational data into structured intelligence, and deploys AI agents that automate complex business processes.

Backed by Accel and DST Global, the company already partners with Fortune 500 organizations including CVS Health, Aon, and PVH. As one of the earliest AI engineers on the team, you'll own the application layer of the platform—building production AI agents, evaluation systems, and LLM-powered features that customers rely on every day.

• Design, build, and deploy production AI features from initial prototype through customer launch.
• Develop AI agents, orchestration pipelines, and prompt systems that solve real enterprise workflows.
• Improve AI output quality through prompt engineering, model selection, retrieval strategies, and structured evaluations.
• Design evaluation frameworks that measure production quality, identify regressions, and continuously improve AI performance.
• Build reliable agent workflows using function calling, structured outputs, tool use, and multi-step reasoning.
• Partner closely with Product Engineering to translate business requirements into scalable AI capabilities.
• Collaborate with the AI Platform team to deploy AI systems on highly reliable production infrastructure.
• Evaluate emerging foundation models, agent frameworks, and AI techniques to improve quality, latency, and cost.
• Develop production software using Type Script, Node.js, Python, and modern cloud infrastructure.
• Help shape the long-term AI architecture powering enterprise automation across the platform.

• 3–8 years of professional software engineering experience building production AI applications.
• Proven experience shipping LLM-powered features used by real customers in production environments.
• Strong software engineering skills using Type Script, Node.js, and/or Python.
• Experience building AI agents, orchestration systems, or autonomous workflows beyond basic retrieval applications.
• Hands-on experience designing prompt systems, evaluation frameworks, and production AI pipelines.
• Familiarity with multiple foundation model providers such as Anthropic, OpenAI, Google Vertex AI, or AWS Bedrock.
• Experience working within early-stage startups or small engineering teams with high ownership.
• Strong product mindset with the ability to iterate quickly while maintaining production quality.
• Bachelor's degree in Computer Science or a related technical discipline.

• Experience building enterprise AI products for vertical SaaS or B2B software companies.
• Familiarity with vector databases such as pgvector or similar retrieval technologies.
• Experience with distributed inference frameworks such as Anyscale Ray or comparable distributed compute platforms.
• Knowledge of post-training techniques, model fine-tuning, or reinforcement learning workflows.
• Experience deploying AI services on AWS Lambda, ECS Fargate, or similar cloud infrastructure.
• Open-source contributions related to LLMs, AI agents, or developer tooling.
• Strong understanding of modern agentic AI techniques beyond traditional RAG or Lang Chain implementations.
• Entrepreneurial mindset with previous founding engineer, startup, or customer-facing engineering experience.

• Base salary: $180,000–$250,000.
• Competitive equity package.
• $1,000 monthly food and commuting stipend.
• Visa support available for E-3 visas, H-1B transfers, and TN visas.
• Five-day onsite collaboration in San Francisco.
• Opportunity to own the AI application layer at one of the fastest-growing enterprise AI startups.
• Work directly with founders and an experienced engineering team building production AI systems at enterprise scale.
• Significant ownership over AI agents, evaluation systems, and customer-facing AI capabilities from the earliest stages of company growth.