Lead Applied AI Platform Engineer — Remote, Equity

Harnham; New York (NY); On-site; USD 297,000 - 402,000; Full time

Benefits offered by this job

Equity

Health insurance

Dental insurance

Vision insurance

Job summary

Harnham is seeking an Applied AI Engineering leader who will own a production LLM platform from architecture to production. This hands-on role involves coding, architectural decisions, and guiding a small team of engineers, data engineers, and data scientists on the East Coast.

You will define system success, manage multi-provider model routing, and own GCP-based deployment pipelines while shaping technical direction and product strategy.

Qualifications

• Extensive production experience shipping LLM applications.
• Strong Python and distributed systems fundamentals.
• Experience leading engineers through code reviews and mentorship.
• Ability to translate stakeholders' requirements into scalable solutions.
• Hands-on with architecture and deployment in cloud environments.

Responsibilities

• Architect and evolve a production LLM platform: orchestration, retrieval, multi-provider routing, and evaluation.
• Stay in the codebase: design, build, and review code with the team, not just direct it.
• Define what 'good' looks like and catch regressions before users.
• Own the GCP infrastructure: pipelines, BigQuery, Cloud Run, IAM.
• Lead a small multidisciplinary team of engineers, data engineers, and data scientists.
• Translate requirements into shipped, scalable solutions.

Skills

LLM platforms

Python

Distributed systems

CI/CD

Leadership

Code review

GCP

Tools

LangChain

LangGraph

OpenAI

Anthropic

Google Gemini

Job description

Harnham is seeking an Applied AI Engineering leader who will own a production LLM platform from architecture to production. This hands-on role involves coding, architectural decisions, and guiding a small team of engineers, data engineers, and data scientists on the East Coast.

You will define system success, manage multi-provider model routing, and own GCP-based deployment pipelines while shaping technical direction and product strategy.