VP AI Engineer: Build Production Multi-Agent Workflows

NorthITE; Boston (MA); Hybrid; USD 230,000 - 320,000; Full time

Job summary

Great Hill Partners seeks a VP, AI Engineer to own the full applied AI lifecycle, from framing business problems to deployment and adoption. The role focuses on the investment team with production multi‑agent workflows, expanding later to portfolio value creation.

It blends hands‑on engineering (75%) with technical leadership (25%) and involves mentoring a junior data scientist. You will collaborate with a Data & Platform Engineer and partner across data, cloud, and integrations to deliver

Qualifications

• 6+ years in AI, software, data, cloud, or related roles.
• Experience designing and deploying production multi‑agent workflows.
• Strong Python and SQL with hands‑on Snowflake experience.
• Experience taking AI systems from prototype to production.
• Knowledge of data pipelines, APIs, cloud infra and CI/CD.
• Proven practice in agentic software development and testing.
• Clear communication with technical and business stakeholders.

Responsibilities

• Own AI use cases end to end from framing to adoption.
• Design, build, and operate multi‑agent workflows for investment teams.
• Create agent harnesses managing goals, context, state, routing, and review.
• Connect agents to firm data and systems via APIs and enterprise integrations.
• Build data pipelines and services to production.
• Evaluate models, manage vendors, and ensure strong user outcomes.
• Mentor junior data scientists and guide contractors.

Skills

Python

SQL

AI systems

CI/CD

Cloud infra

Agent workflows

Education

Bachelor's degree in a technical field

Tools

Snowflake

Claude Code

Codex

OpenAI Agents SDK

Lang Graph

Job description

Great Hill Partners seeks a VP, AI Engineer to own the full applied AI lifecycle, from framing business problems to deployment and adoption. The role focuses on the investment team with production multi‑agent workflows, expanding later to portfolio value creation.

It blends hands‑on engineering (75%) with technical leadership (25%) and involves mentoring a junior data scientist. You will collaborate with a Data & Platform Engineer and partner across data, cloud, and integrations to deliver