Lead AI Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Lead AI Engineer (AI): Designing and delivering production AI systems and orchestration layers for insurance workflow automation with an accent on scalability, reliability, and low-latency inference. Focus on architecting LLM-based pipelines, implementing observability, and leading the technical execution of a global engineering team.
Location: Remote (United States)
Company
Southeast Asia's largest digital insurance platform building AI-powered products to simplify financial services for millions of users.
What you will do
- Lead the design and development of production AI systems powering insurance workflow automation.
- Architect AI orchestration layers connecting LLMs, backend services, and business workflows.
- Own end-to-end AI system design, including inference pipelines, routing, caching, and fallback strategies.
- Drive engineering decisions regarding latency, reliability, cost, and scalability of AI services.
- Lead the implementation of observability systems, including logging, monitoring, tracing, and alerting.
- Mentor engineers and define engineering standards to elevate technical execution across teams.
Requirements
- Strong backend or AI engineering experience in production environments.
- Experience building and scaling AI systems (LLMs, embeddings, or automation workflows).
- Strong system design skills with experience in distributed systems.
- Experience with production inference pipelines and AI orchestration.
- Proficiency in Python, Node.js, and SQL/NoSQL databases.
- Must be based in the United States
Culture & Benefits
- High-ownership culture working in small, cross-functional teams to solve real-world problems.
- Opportunity to work on AI-powered products with international impact.
- Dedicated learning and development budget to support continuous technical growth.
- Fully remote work arrangement within a globally distributed organization.
- Competitive compensation package.
Hiring process
- Evaluation of applications by the technical team.
- 3 to 4 interviews conducted via virtual meetings or onsite.
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