Principal Engineer – AI Security Developer
lead
EngineeringSecurity
0 views0 saves0 applied
Quick Summary
Key Responsibilities
AI Security Strategy: Define and own the multi-year technical strategy and roadmap for AI-powered security capabilities,
Technical Tools
EngineeringSecurity
Responsibilities
~3 min read- →AI Security Strategy: Define and own the multi-year technical strategy and roadmap for AI-powered security capabilities, translating business and risk priorities into a sequenced engineering direction.
- →Reference Architecture: Design and govern the target architecture for StoneX’s AI security platform, including LLM services and orchestration, agent frameworks, RAG and knowledge pipelines, evaluation infrastructure, data access patterns, and integrations across the security environment.
- →Platform Engineering: Architect and build shared platform capabilities including secure LLM services, agent runtimes, tool and connector frameworks, retrieval services, prompt and model management, and observability that allow teams to deliver AI solutions quickly, consistently, and securely.
- →Hands-On Engineering: Remain deeply technical by personally designing and building complex and critical components, prototyping new approaches, and helping teams solve difficult engineering problems across the full stack.
- →Technical Decision-Making: Lead evaluation of models, frameworks, vendors, and open-source technologies and make recommendations based on security, performance, cost, maintainability, and long-term strategic value.
- →Portfolio Prioritization: Partner with security leadership to identify, size, and prioritize high-impact AI opportunities across detection, response, vulnerability management, identity, cloud, application security, and other security domains while challenging work that does not demonstrate meaningful value.
- →Secure Integration: Establish patterns for integrating AI services and agentic workflows with security technologies including source-code repositories, threat models, cloud platforms, SIEM, SOAR, IAM, CMDB, and vulnerability management systems while enforcing appropriate least privilege, auditability, and human oversight.
- →Production Excellence: Establish expectations for reliability, scalability, latency, monitoring, operational readiness, and cost management across production AI workloads.
- →AI Security & Assurance: Serve as a technical authority on securing AI systems against prompt injection, data leakage, model and supply-chain risk, agent tool misuse, adversarial manipulation, and other emerging threats.
- →Evaluation & Quality: Establish how StoneX evaluates LLM and agent performance through benchmark datasets, automated evaluation pipelines, red teaming, regression testing, and measures of accuracy, hallucination, reliability, and analyst trust.
- →Responsible AI: Partner with Risk, Compliance, Legal, Data Governance, and Architecture to ensure AI capabilities meet regulatory, model risk management, privacy, and data residency expectations.
- →Engineering Standards: Set and champion standards for AI engineering, including architecture, code quality, design review, testing, CI/CD, documentation, and production readiness.
- →Technical Leadership: Influence technical direction across security, infrastructure, data, and application engineering teams, building consensus and resolving complex cross-team technical challenges without relying on direct authority.
- →Developing Engineers: Mentor senior and staff-level engineers, strengthen AI engineering capability across the security organization, and help shape technical hiring standards and career development.
- →Executive Advisory: Serve as a trusted technical advisor to the CISO, security leadership, and executive stakeholders by clearly communicating technical strategy, trade-offs, risks, and measurable outcomes.
- →Industry Leadership: Represent StoneX within the broader security and AI community through industry engagement, working groups, conferences, publications, or open-source contributions and bring relevant external thinking back into the organization.
- →Experience within financial services or another highly regulated industry.
- →Experience with model risk management, responsible AI, AI governance, or similar regulatory and governance requirements.
- →Industry contributions such as publications, conference presentations, patents, standards participation, or open-source leadership.
- →Bachelor’s or Master’s degree in Computer Science, Cybersecurity, Engineering, or a related field. Equivalent practical experience and non-traditional paths are welcomed.
- Spending at least four days in the office engaging directly with engineers, security teams, architects, and other stakeholders.
- Designing and building critical components of StoneX’s AI security platform, particularly where the technical complexity or organizational leverage is highest.
- Working with security leadership and engineering teams to identify and prioritize AI use cases based on measurable security value, feasibility, and strategic importance.
- Leading architecture and design reviews for AI capabilities that span teams, security domains, or enterprise technologies.
- Evaluating emerging models, agent frameworks, development approaches, vendors, and open-source technologies against StoneX’s security, performance, cost, and maintainability requirements.
- Prototyping new AI capabilities to validate difficult technical concepts before establishing reusable patterns that other engineers can build upon.
- Working with engineering teams to solve difficult integration, architecture, scalability, reliability, or security challenges.
- Reviewing production AI performance, evaluations, model behavior, observability, reliability, and cost to identify opportunities for improvement.
- Threat modeling AI systems and ensuring appropriate protections exist around data access, agent actions, tool execution, model behavior, and other AI-specific risks.
- Mentoring engineers through architecture discussions, design reviews, code reviews, and complex technical challenges.
- Advising security and executive leadership on AI strategy, technical trade-offs, emerging risks, and the practical implications of changes in AI technology.
- You’re a technical leader who still builds – you enjoy setting architecture and direction, but you still want to write production code and personally tackle the problems where your involvement creates the greatest leverage.
- You think beyond individual applications – you naturally look for the shared platforms, patterns, services, and standards that allow many teams to build better and faster.
- You’re practical about AI – you can separate meaningful technological change from hype and focus teams on where AI can produce measurable security outcomes.
- You’re comfortable making hard technical decisions – you can evaluate competing technologies and approaches, make a recommendation, explain the trade-offs, and stand behind the decision.
- You’re security-minded by design – you treat AI as both a defensive capability and an attack surface and consider adversarial behavior from the beginning.
- You’re a multiplier – you want the engineers and teams around you to become stronger because of the architecture, standards, mentorship, and technical guidance you provide.
- You lead through influence – you can establish technical direction and build alignment across teams and stakeholders even when they don’t report to you.
- You’re willing to challenge the premise – if a use case is vague, a vendor claim doesn’t hold up, or AI isn’t the right solution, you’ll say so and redirect attention toward measurable value.
- You’re continuously learning – you follow AI and security research closely, evaluate emerging technologies critically, and bring back what can genuinely improve StoneX’s capabilities.
- You’re a versatile communicator – you can explain complex AI concepts and strategic trade-offs to executive audiences while still being able to go deeply technical with engineers and researchers.
Requirements
~1 min read- 4 days' work from office.
Location & Eligibility
Where is the job
Not specified
Location terms not specified
About this job
- Posted
- 731 days ago
Listing Details
- Posted
- November 5, 2024
- First seen
- November 5, 2026
- Last seen
- November 6, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 17%
- Scored at
- November 6, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
External application
4 other jobs at
View all →Browse Similar Jobs
Devops Engineer5.9kEngineering Manager4kFullstack Developer3.8kQa Engineer3.7kElectrical Engineer3.1kMechanical Engineer3.1kSoftware Architect2.9kProject Engineer2.8kDesign Engineer2.6kSecurity Engineer2.5kQuality Engineer2.2kBackend Developer2.1kProcess Engineer1.8kFrontend Developer1.4kApplication Engineer1.3kProduct Engineer1.2kAutomation Engineer1kEmbedded Engineer1kCivil Engineer999Mobile Developer969
Newsletter
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
A
B
C
D
No spam. Unsubscribe at any time.