Build the self improvement loop end to end, design and build the experience for non-technical people, own sharing and distribution, and develop evaluation infrastructure for AI-powered productivity tools.
Compensation
$215k to $325k base salary for US-based hires, plus meaningful equity
Responsibilities
Build the self improvement loop end to end: capture evidence from real work, propose improvements, evaluate them, and make the ones that help available for future work.
Build the skill runtime: discovery, retrieval, loading, and composition inside the agent loop.
Build the pipeline that turns session history into new skills, new memories, and improvements to existing ones, and the review surfaces where a person accepts, edits, or rejects them.
Design and build the experience for non-technical people: what Bonsai learned, why it suggests it, and how to review, change, or undo it.
Build evals for improvements: task suites, graders, and production signals that tell us whether a change helped.
Building and operationalizing agentic AI platforms, machine learning platforms, and data pipelines to power business use cases.
Compensation
The anticipated wage for this position is $69,000 - $165,000
Responsibilities
Design and build the engineering backbone for AI and ML systems, including orchestration frameworks, end-to-end data and model pipelines, serving infrastructure, and evaluation/monitoring.
Partner closely with data scientists to productionize models and agentic workflows.
Work with technical product managers, business, and field teams to bring solutions into secure and auditable applications.
Reuse infrastructure and patterns to ensure new business use cases ship faster and cheaper.
Build and operationalize agentic AI platforms (agent-to-agent orchestration, multi-agent workflow engines, tool/API integration).
Requirements
Master’s degree in Computer Science
Master’s degree in Computer Engineering
Master’s degree in Data Science
Master’s degree in a related quantitative or technical field
Lead AI product development and ownership within the Global Private Bank’s AI & Innovation team, designing prototypes, evaluating solutions, and driving Labs-to-Products transition.
Compensation
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
Responsibilities
Design, code, and build AI prototypes hands‑on from end to end
Partner with advisors and business teams to identify high‑value problems and translate them into technical solutions
Own the product vision, priorities, and deliverables for AI innovation initiatives
Define and run evaluations that measure solution accuracy, reliability, risk, user experience, and business value
Work with Technology, Architecture, Data, Cybersecurity, and Controls to address security, privacy, data quality, auditability, and regulatory requirements
Lead Product Security engineering across AI-assisted software development, AI-enabled products, and AI systems, translating AI security requirements into scalable controls, testing, and enforcement across PayPal's products and business units.
Locations (2)
Chicago, Illinois, United States
Austin, Texas, United States
Compensation
The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is: Chicago, Illinois: ($178,500.00 - $265,100.00 Annually) Austin, Texas: ($178,500.00 - $265,100.00 Annually) Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
Responsibilities
Recognized as a security expert, independently resolving the most complex security challenges
Define methods and procedures for new or special assignments
Lead complex, high-impact security projects
Possess a keen awareness of the broader impact of decisions
Design, implement, and operate controls for AI-assisted software development
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