Lead and own backend systems and AI-driven features for Postscript’s SMS marketing platform.
Locations (2)
United States
Canada
Compensation
Salary range of USD $175,000–$220,000 base plus significant equity (we do not have geo-based salaries)
Responsibilities
Take deep ownership of systems and product areas on your team — becoming the go-to technical expert for what you own
Independently investigate, design, and execute solutions across distributed systems with a high degree of ambiguity
Architect, build, and maintain highly available, scalable REST APIs and backend services for internal and external use
Drive system decoupling, modularization, and technical debt reduction — improving long-term maintainability without blocking near-term delivery
Build agentically as your default: leveraging concurrent autonomous agent workflows, owning the output, and keeping a steady queue of aligned work moving
Senior Staff Software Development Engineer - Java, API to join the Zero Trust Exchange team, shaping the future of Zscaler technology, especially with the Zscaler Client Cloud Platform.
Compensation
Base Pay Range
$180,000—$225,000 USD
Responsibilities
Take the Zscaler Client Connector Cloud service to the next level in terms of reliability, availability and scalability
Be a key decision-maker for all things related to product architecture
Collaborate closely with architects from other product areas on the roadmaps
Lead AI Engineer responsible for building secure, production AI applications that orchestrate large language models, enterprise APIs, and Automation Anywhere bots within Paramount’s Platforms & Intelligent Automation team.
Compensation
Hiring Salary Range: $156,800.00 - 235,200.00.
Responsibilities
Architect and build secure, full stack AI applications using Python, TypeScript, APIs and React or similar user interface frameworks.
Integrate LLMs, including Gemini, Claude, GPT and open weight models through Vertex AI and Azure OpenAI, with enterprise systems, MCP tool servers and Automation Anywhere A360 and Agentic Process Automation bots.
Support workflows across ERP, HR, ITSM, finance close, electronic signatures and collaboration platforms.
Implement coordination across multiple agents using planner and worker, supervisor and handoff patterns with Google Agent Development Kit, Agent Engine, LangGraph or equivalent tools.
Build deterministic guardrails, approval gates, role based permissions and complete audit trails so automated actions are explainable, attributable and reversible.
Requirements
Bachelor’s degree in Computer Science, Engineering or a related field
Nice to have: Automation Anywhere agentic capabilities
Director, Data Scientist - Global Payment Network. This role involves partnering with a cross-functional team to deliver products using machine learning and AI agents to drive foundational, scalable intelligence capabilities across the payments ecosystem, supporting fraud/risk, merchant acceptance, and merchant intelligence.
Locations (4)
McLean, Virginia, United States
New York, New York, United States
Riverwoods, Illinois, United States
Chicago, Illinois, United States
Compensation
McLean, VA: $269,100 - $307,200 for Dir, Data Science
New York, NY: $293,600 - $335,100 for Dir, Data Science
Riverwoods, IL: $244,700 - $279,200 for Dir, Data Science
Chicago, IL: $244,700 - $279,200 for Dir, Data Science
Serve as a technical expert across a complex platform, with a particular emphasis on APIs, integrations, and production reliability, taking ownership of critical technical escalations.
Compensation
Annual base salary ranging from $90,000 to $110,000 USD, depending on experience, skills, responsibilities, and business considerations.
Responsibilities
Serve as a subject matter expert on the platform, APIs, integrations, and customer environments.
Troubleshoot complex production issues and API integration challenges involving authentication, connectivity, and configuration.
Own critical technical escalations and lead investigations into Severity 1 (Sev1) incidents.
Collaborate with Engineering, Product, and Customer Success teams to resolve issues and support successful deployments.
Conduct root cause analyses, identify recurring problems, and recommend long-term corrective actions.
Lead technical design and development of high-volume, low-latency applications for mission‑critical systems, providing hands‑on leadership across product, architecture, data, infrastructure, and business teams.
Compensation
Pay Range: $140,500.00 - $234,100.00
Responsibilities
Lead and actively participate in the design and development of high-volume, low-latency applications for mission-critical systems
Collaborate with Product Owners and Product Managers to translate business challenges into technical solutions and support sprint planning and product demonstrations
Conduct technical assessments of risks and issues and document recommendations to support decision-making
Coordinate solution design with Architecture, Data, Infrastructure, and Business teams to support prioritized business outcomes and speed to market
Coach and mentor engineers during development and production implementation, including the creation and maintenance of technical documentation aligned with SDLC guidelines
Requirements
BS or advanced degree in Computer Science, Information Technology, Engineering, or a related field
Nice to have: advanced degree in Computer Science, Information Technology, Engineering, or a related field
Nice to have: SwaggerHub for API design and documentation
Nice to have: cloud transformation strategies across AWS, Azure, and GCP
Nice to have: DevSecOps methodologies and practices
Build and support internal application features and workflow automation that help teams work more efficiently. Turn agreed requirements into secure, tested software using established engineering patterns.
Compensation
$115,000—$175,000 USD
Responsibilities
Implement scoped application features and workflow automations using agreed requirements, acceptance criteria, established patterns, and reusable components rather than duplicate functionality.
Build APIs and system-of-record integrations with input validation, clear errors, and safeguards against duplicate transactions, using reviewed platform interfaces.
Write automated tests for feature behavior, authorization, and integration failures; deliver reviewed changes through established CI/CD pipelines and controlled releases.
Apply approved permissions, secrets management, and sensitive-data controls; add useful diagnostics, investigate assigned feature failures, and document support and recovery steps.
Demonstrate features to process owners, incorporate scoped feedback, and coordinate interface changes; escalate business-policy questions and shared architecture decisions.
Requirements
Nice to have: Internal tool delivery
Nice to have: Workflow automation
Nice to have: Enterprise application integration
Nice to have: Application diagnostics improvement
Nice to have: Automated release workflow improvement
Responsible for the fiscal management of a department or significant business unit, overseeing budgets, financial planning, and cost analysis for the Basic Science Consortium.
Partner with a cross-functional team of data scientists, business analysts, data engineers and product managers to deliver a product customers love.
Compensation
McLean, VA: $197,300 - $225,100 for Mgr, Data Science
Responsibilities
Partner with a cross-functional team of data scientists, business analysts, data engineers and product managers to deliver a product customers love
Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex interpersonal skills to translate the complexity of your work into tangible business goals
Requirements
Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 6 years of experience performing data analytics
Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 4 years of experience performing data analytics
PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics
Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Translate the complexity of work into tangible business goals
Requirements
Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
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