Lead advanced technology projects as an individual contributor, providing expertise across the full software development lifecycle and technical leadership within the Derivatives Credit Risk Technology Team.
Responsibilities
Deliver advanced technology projects across the full software development lifecycle
Serve as advisor or coach to mid-level/junior developers and analysts
Provide technical leadership on projects implemented by the wider team of Software Engineers/Analyst Developers
Collaborate effectively with a large global team of software engineers, business analysts, dev-ops and support staff
Requirements
Bachelor’s/Master’s degree in Computer Science/Engineering/STEM subject
Technical authority for Venmo’s data platform infrastructure and performance engineering, setting technology vision, defining architectural direction, and providing deep technical leadership for mission‑critical databases, data pipelines, messaging systems, caching infrastructure, and performance engineering.
Locations (2)
San Jose, California, 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: Primary Location | Pay Range: San Jose, California: ($218,000.00 - $323,950.00 Annually) Additional Location(s) | Pay Range: Austin, Texas: ($198,000.00 - $294,250.00 Annually) Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.
Responsibilities
Increases results & effectiveness of all software engineers in a large domain
Sets the technology roadmap for a domain
Adapts their role to the need, selecting the most effective means of realizing their technical goals
Provides advice and counsel to senior executives within PayPal, influencing the development of multi-year business strategies
Staff SW Engineer- Java backend with GenAI experience
Software Development Engineer responsible for designing, implementing, and improving Java backend services with Generative AI capabilities in a fintech environment.
Responsibilities
Collaborate with stakeholders to determine requirements for product components
Translate functional requirements into system designs
Design and develop product components
Contribute to project estimation
Lead by example in creating, implementing, and maintaining extensible, reusable code
Requirements
Bachelor's or Master's degree in Computer Science, Software Engineering, Distributed Systems, or related field
Design, build, and maintain real-time equity derivatives pricing and risk systems, implement scalable server-side components, collaborate with portfolio managers and risk teams, contribute to UI components, write documentation, develop automated tests, provide level-3 support and performance tuning.
Compensation
The estimated base salary range for this position is $175,000 to $250,000, which is specific to New York and may change in the future.
Responsibilities
Design, build, and maintain real-time equity derivatives pricing and risk systems (including volatility and PnL components).
Implement robust, scalable, and low-latency server-side components in a multi-threaded environment.
Collaborate with portfolio managers, risk, and middle office to translate business requirements into technical solutions.
Contribute to UI components as needed (and learn new UI technologies where required).
Write clear technical documentation and maintain system design and support guides.
A company-level technical leader for InfluxDB 3.0, focusing on a fast columnar time series database built with Rust, Apache Arrow, and DataFusion.
Responsibilities
Help shape the long-term technical vision for the InfluxDB 3.0 product line and its place in the wider product portfolio.
Partner with other engineering leaders to shape product strategy, roadmap bets and build-vs-buy decisions.
Design and write production Rust for the storage engine: ingestion, compaction, columnar storage on object stores, caching and query execution with DataFusion.
Drive the hardest work in distributed caching, reliability and performance, from benchmarks to production.
Contribute to cloud deployment discussions across AWS and Azure.
Requirements
Advanced degree in computer science or a related field
Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements and take end-to-end ownership of specific subsystems.
Compensation
For Massachusetts Only — The estimated annual salary for this position is between $195,500 – $352,100 annually.
Responsibilities
Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements
Take end-to-end ownership of specific subsystems: architecture, implementation, testing, deployment, on-call, and long-term evolution
Build a working mental model of a highly distributed, complex production system, and make high-leverage contributions
Identify opportunities to continuously evolve the system and tooling
Partner with engineers and applied scientists working at the intersection of distributed systems and statistical/ML-driven decision-making
Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements and take end-to-end ownership of specific subsystems.
Compensation
For New York Only — The estimated annual salary for this position is between $195,000 – $408,000 annually.
Responsibilities
Design, build, and operate core components of a large-scale, real-time distributed decisioning system with strict latency requirements
Take end-to-end ownership of specific subsystems: architecture, implementation, testing, deployment, on-call, and long-term evolution
Build a working mental model of a highly distributed, complex production system, and make high-leverage contributions
Identify opportunities to continuously evolve the system and tooling
Partner with engineers and applied scientists working at the intersection of distributed systems and statistical/ML-driven decision-making
Requirements
B.S. or M.S. in Computer Science, Engineering, or equivalent practical experience
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