Lead AI Engineer, Artificial Intelligence (AI) Required, Work From Home

Gina’s Tech Jobs - IT Recruiting Agency

San Francisco (CA)

Remote

USD 180,000 - 240,000

Full time

14 days+
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Benefits offered by this job

Medical insurance
Dental
Vision
Savings plan
PTO

Job summary

Gina’s Tech Jobs - IT Recruiting Agency is seeking a Lead AI Engineer to own the design, development, and delivery of production AI systems across our backend and workflow automation stack. This fully remote role sits with a global engineering team building reliable, scalable AI services for insurance workflows.

You will lead architecture, observe systems, and mentor engineers, driving end-to-end technical execution in a fast-paced, distributed environment.

Qualifications

  • Strong backend or AI engineering in production environments.
  • Experience building or scaling AI systems (LLMs, embeddings, automation workflows).
  • Strong system design skills with distributed systems experience.
  • 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.

Responsibilities

  • Lead 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.

Skills

Backend engineering
AI engineering
Distributed systems
Observability
Leadership
Docker
Kubernetes
Python
LLM APIs

Tools

Docker
Kubernetes
Node.js
NoSQL
OpenAI
LLM APIs
Python
SQL

Job description

Lead AI Engineer, Artificial Intelligence (AI) Required, 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.

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.
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
  • Strong backend or AI engineering experience in production environments.
  • Artificial Intelligence (AI) experience required.
  • 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, Claude, Distributed Systems Tools, Docker, Kubernetes, LLM APIs, Node.js, NoSQL, Observability Stack (Logging, Metrics, Tracing), OpenAI, Open-Source Models, Python, and SQL.
Benefits

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

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