Staff AI Engineer

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San Francisco / $200000 - $225000 annum

INFO

Salary
SALARY:

$200000 - $225000

Location

LOCATION

San Francisco

Job Type
JOB TYPE

Permanent

Staff AI Engineer - Agentic Solutions

Location: Onsite - San Francisco or Menlo Park

Compensation: Base to $225,000 + Bonus + RSUs (Total ~ $400,000 annually)

Role Overview

Seeking a Staff-level AI Engineer to lead a high-impact team building and deploying agentic AI solutions at scale across a major financial services institution. This role is responsible for reducing operational costs across millions of transactions by architecting and implementing robust, enterprise-grade agentic systems in the cloud. The solutions built will touch every division and business line, demanding technical rigor and innovative problem-solving.

Responsibilities

  • Lead the design, development, and deployment of agentic AI applications across multiple cloud environments and business units
  • Build production-grade, scalable solutions handling millions of transactions daily in a highly regulated, large-scale FS context
  • Deploy and fine-tune Large Language Models (LLMs) and agentic architectures for enterprise-wide, customer-facing use cases
  • Partner with business stakeholders and engineering leaders to translate enterprise objectives into lasting, measurable value
  • Drive end-to-end AI project development: definition, proof-of-value, robust engineering, deployment, and enterprise integration
  • Mentor and guide a technical team focused on blending ML science and software engineering for scalable, real-world impact
  • Ensure AI systems meet stringent regulatory, security, and compliance standards inherent to the financial industry
  • Contribute to the vision for next-generation, cost-reducing AI solutions that accelerate innovation across the firm

Requirements

  • 8+ years' professional experience developing and delivering large-scale AI/ML solutions in a commercial setting, preferably within a MAANG, leading fintech, or high-velocity unicorn startup
  • Expertise deploying LLMs and intelligent agents in production for enterprise/customer-facing use
  • Strong blend of applied machine learning, MLOps, and software engineering
  • Experience architecting and supporting cloud-native, agentic solutions in highly complex, high-transaction environments
  • Ability to collaborate across cross-functional and business-facing teams, translating sophisticated AI techniques into clear business outcomes
  • Applied experience (not just theoretical or publication-focused) in quantitative investment workflows, such as equities, fixed income, or multi-asset strategies, is a major plus

Nice to Haves

  • Familiarity with the regulatory and compliance landscape of financial services AI deployment
  • Experience building products for large-scale, consumer-facing environments
  • Hybrid background in both applied research (not solely academic) and hands-on engineering

CONTACT

Gabriella Varela

Recruitment Consultant

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