The Execution Risk team identifies, measures, monitors, manages and reports on risks across the firm’s portfolios. The team works to prevent financial loss from malfunctioning or mis controlled trading systems and protect the firm from regulatory failures.
Responsibilities
Identifies, measures, monitors, manages and reports on risks across the firm’s portfolios
Prevent financial loss from malfunctioning or mis controlled trading systems
Protects the firm from regulatory failures
Assess proposed new and materially modified algorithm documents and their pre- and post-trade controls, with authority to approve, reject and require remediation
Verify that controls are implemented as documented and are appropriate for each strategy, product
Requirements
Nice to have: Prior sign-off accountability through supervision, approval authority or incident ownership
Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Responsibilities
Expected to be an SME, collaborate and manage the team to perform.
Responsible for team decisions.
Engage with multiple teams and contribute on key decisions.
Provide solutions to problems for their immediate team and across multiple teams.
Lead efforts to identify and implement best practices within the team to improve productivity and quality.
Junior contributor working with software engineering team on business travel booking platforms, advancing REST APIs, developing new features, and supporting platform operations.
Responsibilities
Monitor and support existing platform processes
Manage back‑office support contracts and engineers
Capture requirements and build solutions
Troubleshoot and resolve production issues
Requirements
Nice to have: AI-related opportunities and solutions
Lead the AI roadmap and product strategy for business applications across multiple enterprise domains, driving innovation and impact in a cybersecurity context.
Compensation
The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.
Responsibilities
Own and prioritize an AI-powered roadmap tailored to business applications across Sales, Licensing, Finance, Support, Customer Success, and BI & Data Analytics.
Partner with business leaders to identify bottlenecks and apply AI/Agentic workflows to streamline critical enterprise journeys.
Build and iterate on functional prototypes using AI-native tools and low-code platforms to validate AI agent interactions with enterprise APIs.
Define error budgets, accuracy guardrails, and compliance standards for AI outputs in business-critical systems.
Create and version-control Golden Sets to grade AI model performance in real-world business scenarios.
The Systems Engineer II works under supervision and uses established procedures to perform engineering duties in researching, planning, designing, and developing products for use in the Aerospace or Electronics marketplace.
Compensation
Salary range: $105,000 - $123,000.
Responsibilities
Work effectively with all functional groups to achieve product performance and cost targets.
Build quality and manufacturability into the design.
Define/understand/comply with company and regulatory guidelines to assure a safe operating environment.
Model Based Systems Engineering – create and maintain models and perform what if and use cases utilizing simulation.
Demonstrate proficiency with verbal and written English for technical reports, presentations, analyses, or other communications.
Requirements
BA or BS Degree in an engineering discipline
Mechanical preferred
Nice to have: Mechanical Engineering degree
Nice to have: Master’s Degree in Engineering
Nice to have: Experience with application of Artificial Intelligence in engineering or aerospace systems
Lead enterprise-wide AI enablement programs, translating strategy into executable technical programs and coordinating across engineering, platform, IT, security, privacy, legal, procurement, risk, and business stakeholders.
Responsibilities
Own the end-to-end lifecycle of complex AI enablement programs, from intake, discovery, and proof of concept through production rollout, adoption, and ongoing operationalization.
Translate enterprise AI strategy into clear roadmaps, milestones, program plans, dependencies, success measures, and delivery commitments.
Define program scope, goals, technical and operational readiness criteria, and measurable outcomes in collaboration with engineering and business stakeholders.
Drive prioritization across concurrent AI initiatives based on business value, technical readiness, risk, capacity, and organizational impact.
Develop and maintain integrated schedules, risk assessments, issue logs, decision records, and mitigation plans for high-impact programs.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical field
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