below marketmost similar roles pay hereabove market
This role pays less than
74%
of similar roles. Most pay
$159,437–$221,850
— the blue band above.
At the midpoint, this role pays about
$161k
versus about
$191k
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 230 roles with salary data.
JOB TITLE: Offensive AI Engineer – Frontier AI Security & Testing, VP
The Offensive AI Engineer – Frontier AI Security & Testing, VP joins the Frontier AI Security & Testing team within Regulatory Assurance, Penetration Testing & Offensive Research. This engineering role involves designing, deploying, and troubleshooting secure AWS-based platforms, evaluation harnesses, and data pipelines to utilize frontier AI models as an offensive security capability. You will build infrastructure-as-code using Terraform or CloudFormation, manage Amazon Bedrock and SageMaker environments, and develop agentic workflows using LangGraph, Strands, or CrewAI. Key responsibilities include building Databricks pipelines with PySpark and SQL, integrating REST APIs, and implementing technical controls like guardrails and kill-switches. You will solve the problem of using AI for adversary emulation and threat hunting within a highly regulated financial services environment while ensuring auditable, governed model behavior.
Design and deploy secure, isolated AWS environments to host frontier AI models using Bedrock, SageMaker, and EKS.
Build and maintain infrastructure-as-code and CI/CD pipelines for repeatable and auditable AI workload deployments.
Engineer network segmentation, identity controls, and secrets management to create trust boundaries for agentic AI activity.
Develop model-agnostic abstraction layers and standardized evaluation harnesses to benchmark model precision and reliability.
Build agentic workflows and multi-agent orchestration patterns to support reconnaissance and adversary simulation.
Design Databricks pipelines to ingest and analyze model telemetry, evaluation results, and offensive security data.
Implement technical guardrails, human-in-the-loop checkpoints, and kill-switch mechanisms to limit agent autonomy.
Engineer full logging and observability systems to capture agent decision paths for audit and regulatory review.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Artificial Intelligence, or equivalent practical experience.
5+ years of hands-on experience in software, cloud, data, or security engineering.
2+ years of hands-on experience building and deploying GenAI, LLM, or agentic AI solutions on cloud platforms, preferably AWS.
Deep hands-on experience deploying AI-enabled applications on AWS, including Bedrock, SageMaker, Lambda, API Gateway, EKS/ECS, IAM, KMS, and VPC networking.
Strong Python skills and experience with GenAI and agentic frameworks such as LangChain, LangGraph, Strands, CrewAI, Pydantic, or MCP.
Hands-on Databricks experience with PySpark, SQL, Delta Lake, and workflows, plus a grounding in data science and statistical analysis.
Experience with infrastructure-as-code (Terraform preferred) and CI/CD tooling.
AWS certifications, Databricks certifications, offensive security certifications, or experience in financial services are preferred.
Penetration Testing
Red Teaming
Python
Go
AWS
Azure
GCP
Burp Suite
Cobalt Strike
Mythic
Sliver
BloodHound
MITRE ATT&CK
OWASP Top 10
Splunk
Databricks
PySpark
osquery
Vulnerability Research
Exploit Development