VP of AI/ML Systems & Platforms

ARCHER; New York (NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive Compensation

Wellbeing Programs

Flexible Global Resources And Tools

Paid Leave

Paid Volunteer Time

Job summary

ARCHER designs and builds production agentic AI systems, including end-to-end RAG workflows, vectorization pipelines, and intelligent document processing services. You will own major AI platform components, drive enterprise integration, mentor engineers, and partner with stakeholders to deliver reliable AI solutions.

The role emphasizes collaboration, strong Python expertise, and robust API design, with focus on testing, documentation, and governance across projects.

Qualifications

• Requires a bachelor's degree in Computer Science, Engineering, or a related field and at least six years of software engineering experience.
• Two or more years building production AI/ML systems; an advanced degree is preferred.

Responsibilities

• Design and build production agentic AI systems, end-to-end RAG and vectorization pipelines, and intelligent document processing services, including APIs, evaluation harnesses, and data governance controls.
• Own significant AI platform components, contribute to enterprise platform integration, mentor engineers, and collaborate with stakeholders to deliver reliable AI solutions.

Skills

Agentic AI

RAG

Python

LLM Integration

Document Processing

API Design

Testing

Collaboration

Communication

Mentoring

Education

Bachelor's degree in Computer Science, Engineering, or related field

Advanced degree preferred

Tools

FastAPI

Vector Databases

Embedding Models

OCR

Pytest

Java

Spring Boot

Job description

ARCHER designs and builds production agentic AI systems, including end-to-end RAG workflows, vectorization pipelines, and intelligent document processing services. You will own major AI platform components, drive enterprise integration, mentor engineers, and partner with stakeholders to deliver reliable AI solutions.

The role emphasizes collaboration, strong Python expertise, and robust API design, with focus on testing, documentation, and governance across projects.