Lead Vulnerability Research Engineer, IT Security

Location: St. Petersburg

Job Description Summary
The financial services industry is continuously targeted by sophisticated cyber adversaries ranging from criminal organizations to nation-state actors. Raymond James relies on the Cyber Threat Center (CTC) to identify, assess, and reduce technology risk across the enterprise.

The Lead Vulnerability Research Engineer will be a hands-on technical leader within Vulnerability Management, responsible for discovering, validating, and operationalizing knowledge of vulnerabilities that present credible risk to the firm. The role combines threat-informed vulnerability research, offensive security, software engineering, data analysis, and security automation. The engineer will investigate emerging vulnerabilities and attack techniques; determine exploitability, reachability, and enterprise relevance; and convert research into repeatable detection, prioritization, validation, and remediation capabilities at scale.

The engineer will responsibly apply AI-assisted techniques to accelerate hypothesis generation, code and patch analysis, test development, finding correlation, exploit-path reasoning, and remediation guidance. AI output must remain subject to rigorous human validation, security and privacy controls, reproducibility standards, and measurable quality outcomes. The role will partner across threat intelligence, security operations, application security, infrastructure, cloud, engineering, architecture, and technology risk teams to reduce exposure before adversaries can act.

Job Description

This position follows a hybrid work model, with an expectation to be in the office 3 days per week at the St. Petersburg, FL Corporate Office location.

Please note:
This role is not eligible for Work Visa sponsorship, either currently or in the future.

Responsibilities

• Lead threat-focused vulnerability research across enterprise applications, APIs, operating systems, network devices, cloud services, containers, open-source components, commercial products, and emerging AI-enabled technologies.
• Continuously analyze threat intelligence, vendor advisories, public exploit research, malware and campaign reporting, security-research disclosures, and internal telemetry to identify vulnerabilities with credible relevance to the enterprise.
• Perform authorized, controlled technical research to validate vulnerability conditions, affected versions, attack prerequisites, exploitability, reachability, likely impact, and available mitigations without creating unnecessary operational risk.
• Reproduce vulnerabilities in isolated lab environments; analyze patches, source code, binaries, configurations, protocols, and proof-of-concept artifacts; and create defensible evidence that distinguishes theoretical exposure from actionable risk.
• Develop safe detection and validation content such as authenticated checks, queries, signatures, scripts, test harnesses, configuration assessments, and exposure analytics. Ensure research artifacts are reviewed, version-controlled, documented, and designed to avoid disruption.
• Build production-quality automation and integrations that ingest, normalize, enrich, correlate, deduplicate, prioritize, ticket, route, retest, and close vulnerability findings across scanners, asset inventories, threat-intelligence sources, software inventories, cloud platforms, endpoint tools, and engineering systems.
• Create threat-informed prioritization models that incorporate active exploitation, adversary behavior, exploit maturity, internet exposure, asset criticality, application context, business service dependency, reachability, compensating controls, data sensitivity, and remediation feasibility.
• Use AI-assisted research capabilities to summarize technical evidence, identify likely vulnerable code paths, compare patches, generate and refine test hypotheses, correlate findings, propose validation steps, and draft remediation guidance.
• Evaluate and govern AI-assisted security workflows for accuracy, hallucination, prompt injection, insecure output, sensitive-data exposure, excessive agency, model and dependency supply-chain risk, reproducibility, auditability, and appropriate human oversight.
• Design human-in-the-loop controls and benchmark AI-assisted workflows using measurable outcomes, including precision, recall, false-positive and false-negative rates, analyst time saved, validation quality, remediation quality, and reduction in time to protective action.
• Provide rapid technical analysis for high-risk and actively exploited vulnerabilities, including concise impact assessments, affected-asset logic, interim mitigations, detection opportunities, validation procedures, and executive-ready risk communication.
• Conduct root-cause and recurring-pattern analysis to identify systemic weaknesses in technology selection, configuration, software dependencies, asset visibility, patch processes, or control coverage; recommend durable preventive improvements.
• Partner with remediation owners to explain technical risk, validate fixes and…