Technology Financial Operations AI & Automation Engineer

State Street

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Quincy, MA
Salary
$70,000–$118,750 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $174k
This role $94k
$53k $229k
below market most similar roles pay here above market

This role pays less than 98% of similar roles. Most pay $142,972–$204,200 — the blue band above. At the midpoint, this role pays about $94k versus about $174k for comparable roles.

Based on 240 similar postings.

Employer

About State Street

State Street Corporation is one of the world''s largest custodian banks and asset managers, providing investment servicing, investment management, and investment research to institutional investors. Industry: Financial Services & Asset Custody

State Street currently has 330 open roles on FindRole.

Listed pay typically runs $120,000–$202,500 across 223 roles with salary data.

Most-posted roles

View all roles at State Street

At a glance

TL;DR · Technology Financial Operations AI & Automation Engineer

The Technology Financial Operations AI & Automation Engineer joins the Technology Financial Operations Office to build and support AI-enabled workflows that modernize recurring routines. This role involves identifying automation opportunities across technology cost, Cloud FinOps, TCO, procurement, and headcount reporting to replace manual spreadsheet checks with governed automation. You will map business processes, translate requirements into workflow designs, and deploy solutions using the Microsoft Power Platform, Power Automate, Copilot Studio, SharePoint, and Power BI. The position requires utilizing SQL, Python, and APIs to create retrieval-based assistants and routing agents. You will solve technical problems related to intake triage, accrual checks, and productivity tracking while ensuring all solutions remain compliant with data governance, auditability, and responsible AI patterns within a complex, matrixed financial operations environment.

What you'll do

  • Identify and prioritize automation opportunities across technology financial operations based on value, risk, and maintainability.
  • Map current business processes with SMEs to translate requirements into workflow designs and control points.
  • Build and deploy automations using Microsoft Power Platform, workflow technologies, and AI-enabled productivity tools.
  • Implement AI for intake triage, knowledge assistance, document review, and human-in-the-loop decision support.
  • Automate routines for TCO, FinOps, procurement, headcount, and operational reporting to reduce manual effort.
  • Manage automations as products by providing documentation, monitoring, release discipline, and user guidance.
  • Ensure all solutions are compliant, auditable, and secure by partnering with security, risk, and audit teams.
  • Track performance metrics including effort avoided, cycle-time reduction, error reduction, and user adoption.

What we're looking for

  • Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Finance, Business Analytics, Engineering, or a related field (preferred).
  • Experience designing, building, and supporting workflow automations, low-code solutions, AI-enabled assistants, or similar enterprise productivity tools.
  • Hands-on experience with Microsoft Power Platform, Power Automate, Copilot, SharePoint, Power BI, or comparable enterprise automation technologies.
  • Experience mapping business processes, documenting requirements, and designing future-state workflows for non-technical stakeholders.
  • Experience with enterprise AI or agentic workflow patterns, including retrieval-based assistants, knowledge bases, and workflow copilots.
  • Experience with financial services, technology business management, FinOps, IT TCO, procurement, or technology finance operations.
  • Familiarity with Microsoft Fabric, Dataverse, APIs, SQL, Python, or other data and integration approaches.
  • Experience operating under SDLC, model risk, data governance, responsible AI, or similar control frameworks.

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