below marketmost similar roles pay hereabove market
This role pays more than
78%
of similar roles. Most pay
$174,950–$214,925
— the blue band above.
At the midpoint, this role pays about
$225k
versus about
$195k
for comparable roles.
Based on 240 similar postings.
Employer
About Goldman Sachs
Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.
Goldman Sachs currently has
71 open roles
on FindRole.
Listed pay typically runs
$140,000–$250,000
across 34 roles with salary data.
The VP - Technical Program Manager - Autonomous Alpha Generation Platform leads the vision and cross-functional delivery of a central platform at the intersection of quantitative research, artificial intelligence, and automated trading systems. This role involves driving end-to-end program execution to build a modular, extensible infrastructure that integrates into trading desk workflows. Key responsibilities include architecting pluggable framework interfaces, defining Human-in-the-Loop control mechanisms, and managing MLOps infrastructure for scalable data and feature storage. The candidate will utilize skills in platform engineering, project management, and machine learning to manage time-series data, model registries, and distributed compute orchestration. The work focuses on enabling autonomous AI agents and researchers to explore signal spaces, engineer features, and run high-fidelity simulations while maintaining strict point-in-time integrity and regulatory compliance.
Drive end-to-end project management and program execution for the central platform, establishing delivery milestones and release schedules.
Lead integration initiatives to connect central platform infrastructure with desk-specific applications and strategy frameworks.
Establish SDKs, APIs, and plugin standards to allow internal teams to integrate proprietary capabilities and analytical modules.
Define requirements for Human-in-the-Loop control mechanisms, including approval gates and real-time intervention capabilities.
Partner with front-end engineering to deliver intuitive dashboards and control centers for real-time visibility into agent decisions.
Direct requirements for scalable data and feature infrastructure to ensure point-in-time integrity and dataset lineage tracking.
Establish unified cataloging and metadata searchability to support asset exploration by human researchers and automated agents.
What we're looking for
7+ years of experience in technical program management, platform engineering management, or enterprise software delivery within fintech, investment banking, quantitative hedge funds, or enterprise SaaS.
Demonstrated success leading complex, multi-team infrastructure projects, managing technical roadmaps, and tracking dependencies.
Proven ability to define platform requirements for modular architectures, open plugin frameworks, APIs, and SDKs for internal developer ecosystems.
Hands-on experience defining workflow control points, governance checkpoints, and user-facing monitoring/dashboard interfaces for automated or semi-autonomous software systems.
Demonstrated experience with enterprise MLOps architecture, feature stores, data cataloging, model registries, and automated lineage tracking.
Experience managing time-series data infrastructure, including high-frequency tick data storage, time-series transformations, and point-in-time compliance.
Familiarity with autonomous agent design patterns, quantitative trading concepts, financial markets, or systematic research workflows.
Proficiency with Python (e.g., Pandas, PyTorch, Ray, Celery) and C++ integration patterns (preferred).