Enterprise AI Engineer — Remote (ET Hours) with Equity

Rise Talent Advisors; San Francisco (CA); Remote; USD 160,000 - 240,000; Full time

Benefits offered by this job

Equity

Job summary

Rise Talent Advisors is helping a venture-backed AI startup hire senior AI engineers. The role is remote with a preference for New York; you will work on a customized AI platform for large enterprises, ensuring deployments stay compliant and auditable within customer environments.

You will integrate with a globally distributed team, own architecture-to-deployment tasks, and focus on production-grade back-end and full-stack Python work for AI-powered products.

Qualifications

• 6 to 12 years in back end or AI engineering, building and deploying large language model systems in production.
• Last 2–3 years at a high growth, venture backed Series A–D startup shipping product to enterprise customers.
• LLM or agentic workflows you built and shipped for external customers in production.

Responsibilities

• Own the technical build of a customized version of the AI platform for a major enterprise customer, from architecture to deployment.
• Adapt and extend the core platform for the customer's environment, merging customer work back into the main product.
• Work daily with core engineering team abroad, overlapping on Eastern time.
• Own production deployments, integrations and reliability of LLM systems in a regulated enterprise environment.
• Build back end and full stack features in Python: APIs, integrations and deployments for AI powered products.

Skills

Python backend

Production deployments

Enterprise customer experience

Education

Bachelor's degree in Computer Science

Tools

Kubernetes

CI/CD

Observability tooling

Job description

Rise Talent Advisors is helping a venture-backed AI startup hire senior AI engineers. The role is remote with a preference for New York; you will work on a customized AI platform for large enterprises, ensuring deployments stay compliant and auditable within customer environments.

You will integrate with a globally distributed team, own architecture-to-deployment tasks, and focus on production-grade back-end and full-stack Python work for AI-powered products.