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KeyBank

Provides banking, loans, and financial services

Infrastructure Optimization & AI Technical Lead

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • At least 5 years of professional software development experience, with deep proficiency in Python, including modern asynchronous patterns, typing, and Pydantic v2.
  • At least 4 years of hands-on architecture and engineering experience on Google Cloud Platform, including Cloud Run, Cloud Functions, Pub/Sub, Cloud Scheduler, BigQuery partitioning, clustering and policy tags, Cloud Storage, Cloud Spanner, Secret Manager, IAM roles and service accounts, and workload identity federation.
  • Direct experience architecting applications using Google Vertex AI, including Gemini models, Agent Builder, Search, grounding pipelines and vector embeddings, or frameworks such as LangChain or LangGraph.
  • A demonstrated track record designing distributed systems, RESTful APIs, event-driven pipelines, and canonical data models.
  • Ability to lead squads, mentor developers, define architectural standards, and drive consensus across engineering, product, and platform leadership.
  • A bachelor's degree in Computer Science, Software Engineering, or Mathematics, or equivalent practical enterprise experience.

Responsibilities

  • Design and implement modular, loosely coupled GCP cloud architectures that scale independently and adhere to enterprise reliability and zero-trust standards.
  • Establish canonical schemas, interface contracts, and reusable platform patterns across ingestion, normalization, storage, and AI reasoning layers.
  • Translate product roadmaps and Architecture Review Board specifications into engineering milestones, technical spikes, and interface contracts.
  • Provide technical mentorship, code reviews, and architectural guidance to squad developers and partner engineering teams across sprints.
  • Develop high-performance, containerized microservices and jobs using Python, FastAPI, and Pydantic v2, hosted on GCP Cloud Run.
  • Build deterministic validation and evaluation engines that isolate critical business logic, such as CIDR mathematics and precedence rules, from probabilistic large language model outputs.
  • Implement strict schema validation and data contracts for structured and unstructured operational telemetry from GitLab, Palo Alto Panorama, ServiceNow, and GCP APIs.
  • Design idempotent pipelines, automated quarantine routing for malformed payloads, and self-healing deployment models.
  • Architect conversational agent workflows using Vertex AI Agent Builder, Gemini, and agentic frameworks such as LangGraph, integrating custom tool routing, memory, and complexity routing.
  • Implement hybrid retrieval combining Spanner Graph, vector embeddings, and Vertex AI Search to support grounded, multi-hop operational reasoning.
  • Ensure AI-generated responses have verifiable evidence citations linking to authoritative rule IDs, commit hashes, or documentation.
  • Partner with QA and AI Assurance teams to implement evaluation pipelines using frameworks such as Braintrust to measure grounding and latency and enforce safety gates.
  • Implement automated testing, container scanning, and zero-touch deployment pipelines for repeatable, immutable cloud releases.
  • Enforce Attribute-Based Access Control, pre-retrieval entitlement filtering, Secret Manager integration, and Model Armor safety filters.
  • Integrate end-to-end tracing across Cloud Logging and Cloud Monitoring, balancing compute performance with GCP cost efficiency.

Desired Qualifications

  • Google Cloud Certified Professional Cloud Architect or Professional Data Engineer certification.
  • Familiarity with enterprise network concepts, including firewalls and CIDR routing, ServiceNow IT Service Management or Knowledge Management, or IT Operations Analytics.
  • Experience building automated large language model evaluation harnesses, prompt regression suites, or synthetic evaluation datasets.
  • Experience with enterprise governance, model risk management, and regulatory compliance within a financial institution.

About the Company

KeyBank

Provides banking, loans, and financial services

KeyBank provides a full range of banking services for individuals, small businesses, and commercial clients across the United States. It offers checking and savings accounts, credit cards, mortgages, loans, and other financial products. Customers use these products by making deposits, borrowing money, or using credit in everyday life; the bank earns interest on loans, fees for services, and commissions on products. KeyBank differs from many rivals by offering a wide geographic footprint and a focus on tailored financial solutions plus tools to improve financial wellness, such as budgeting resources and planning guidance. Its goal is to help clients reach financial milestones—like buying a home, paying down debt, or saving for the future—through a comprehensive set of services.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Cleveland, OH
Founded
1824

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