Lead AI Engineer

Lead AI Engineer (Remote) at Solstice Analytics
Lead AI Engineer, Work From Home
Location: San Francisco, CA, us, Remote
Job Description
Lead AI Engineer, Work From Home
We are looking for a Lead AI Engineer to own the design, development, and delivery of production AI systems across our backend and workflow automation stack.  The Lead AI Engineer role sits at the core of the AI platform, where model capabilities are translated into reliable, scalable, and production-grade systems that directly impact real users and business outcomes.  This is a fully remote role where you will be part of a global engineering team working across multiple countries to build reliable, scalable AI systems.  We have multiple openings for this position.  This position is 100% Remote.
Lead AI Engineer Responsibilities:
\- 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 around latency, reliability, cost, and scalability of AI services.
\- Lead implementation of Observability Systems (logging, monitoring, tracing, alerting).
\- Review and guide backend AI implementation across engineering teams.
\- Collaborate with product, backend, DevOps, and operations teams to ship end-to-end AI features.
\- Debug complex production issues across distributed AI systems and lead root-cause analysis.
\- Define engineering standards and best practices for AI system development.
\- Mentor engineers and elevate technical execution quality across teams.
Lead AI Engineer Outcomes:
\- AI systems operate reliably at scale with strong performance and low latency.
\- AI workflows are stable, observable, and production-grade across multiple products.
\- System architecture supports rapid iteration without compromising reliability.
\- Production incidents are quickly identified, resolved, and prevented.
\- Engineering teams execute faster and with higher technical quality under your leadership.
\- AI capabilities are deeply integrated into global insurance workflows.
Qualifications
Lead AI Engineer Qualifications:
\- Strong backend or AI engineering experience in production environments.
\- Experience building or scaling AI systems (LLMs, embeddings, recommendation systems, or automation workflows).
\- Strong system design skills with experience in distributed systems.
\- Experience with production inference pipelines and AI orchestration.
\- Strong debugging ability in high-scale, latency-sensitive environments.
\- Experience with observability, monitoring, and incident response.
\- Proven ability to lead technical execution in cross-functional teams.
\- Strong ownership mindset and ability to drive projects end-to-end.
\- Comfortable working in fast-paced, globally distributed teams.
\- Tech Stack:  Anthropic, Distributed Systems Tools, Docker, Kubernetes, LLM APIs, Node.js, NoSQL, Observability Stack (Logging, Metrics, Tracing), OpenAI, Open-Source Models, Python, and SQL.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
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Additional Information
All your information will be kept confidential according to EEO guidelines.