AI Engineer
$180,000–$250,000 year
On-siteSan Francisco, California, United States
Job Summary
Design, build, and deploy production AI features from initial prototype through customer launch, developing agents, orchestration pipelines, and prompt systems that solve real enterprise workflows. Improve output quality through prompt engineering, model selection, and structured evaluations while designing frameworks to measure performance and identify regressions. Build reliable agent workflows using function calling, tool use, and multi-step reasoning, partnering with Product Engineering to translate business requirements into scalable capabilities. Collaborate with the AI Platform team to deploy systems on highly reliable infrastructure and evaluate emerging foundation models to optimize latency and cost. Develop production software using TypeScript, Node.js, and Python, helping shape the long-term architecture powering enterprise automation.
Required Qualifications
- 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 TypeScript, 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
Desired Qualifications
- 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 LangChain implementations
- Entrepreneurial mindset with previous founding engineer, startup, or customer-facing engineering experience
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