Staff Talent Operations Engineer

Accountabilities:: Talent Operations Infrastructure: Take end-to-end ownership of the Rippling Applicant Tracking System (ATS), managing its architecture, data structures, templates, workflows, and automations to ensure the platform effectively supports evolving recruitment needs. Recruiting Analytics and Reporting: Develop and maintain recruiting reports, operational funnel metrics, and executive dashboards, ensuring data accuracy, consistency, and reliability to support informed decision-making. Process Optimization: Work directly with recruiters, interviewers, and hiring managers to identify bottlenecks, understand operational challenges, and implement practical improvements throughout the hiring process. Continuous Improvement: Regularly evaluate recruiting workflows, measure operational efficiency, track time savings, and introduce improvements that reduce hiring friction and accelerate recruitment timelines. AI Platform Development: Expand an existing AI-powered hiring application into a comprehensive platform serving recruiters, interviewers, and hiring managers throughout the talent acquisition process. AI Application Engineering: Design, develop, and deploy AI-powered tools using Claude and other large language models, including intelligent agents that support candidate sourcing and coordination through Apollo and Model Context Protocol (MCP) integrations. Production Deployment and Monitoring: Transform experimental AI prototypes into reliable production applications hosted on AWS or comparable cloud infrastructure, implementing appropriate monitoring, security controls, and operational safeguards. Custom Integrations and Automation: Build tailored integrations between recruitment systems and other business platforms, ensuring solutions are scalable, maintainable, and aligned with long-term technical requirements. Security and Compliance: Collaborate with IT, security, and legal teams to ensure newly developed tools and integrations meet organizational security, privacy, and compliance standards without compromising delivery speed. Product and Project Management: Manage talent technology initiatives using structured roadmaps, prioritized backlogs, and regular product releases, ensuring development remains aligned with actual recruiting needs. AI Fluency and Talent Development: Partner with engineering and development teams to design AI literacy and fluency programs, incorporating relevant capabilities into recruitment, interviewing, and talent assessment practices. Technology Adoption and Enablement: Support the successful implementation of new tools through effective communication, training, documentation, and collaboration with nontechnical stakeholders. Requirements: Professional Experience: At least 6 years of experience in recruiting operations, including hands-on ownership and administration of an ATS or HRIS, with strong knowledge of system architecture, data structures, workflows, and reporting. High-Growth Environment: Previous experience working in a fast-paced startup or high-growth organization, with the ability to manage evolving priorities and deliver results in environments with limited documentation. Data Analytics and Reporting: Strong analytical skills and demonstrated ability to build reports and dashboards, interpret recruitment data, identify trends, and detect data quality issues. Process Improvement: Proven experience optimizing recruitment operations, with measurable results such as reduced administrative workload, time savings, improved candidate coordination, or shorter time-to-hire. AI and LLM Development: Practical experience building AI-powered applications using large language models such as Claude, including agents, scheduling assistants, chatbots, workflow automation tools, or similar solutions. Cloud Infrastructure: Experience taking AI applications from prototype to production and operating applications on AWS or a comparable cloud platform. Technical Integration Skills: Ability to develop custom integrations and automate workflows across different platforms, with an understanding of modern APIs and emerging AI integration technologies. Model Context Protocol: Familiarity with building custom MCP connections to integrate AI applications with specialized data sources and business systems is a strong advantage. AI Production Experience: Experience deploying and maintaining business-critical AI applications, including model hosting, performance optimization, token consumption management, and operational monitoring, is highly desirable. Security and Compliance: Demonstrated experience navigating security assessments, privacy requirements, and compliance reviews for internally developed applications and technology solutions. Change Management and Communication: Ability to encourage technology adoption among nontechnical teams through clear communication, practical training, documentation, and ongoing support. Autonomy and Documentation: Comfortable independently managing new technical projects, navigating ambiguity, and creating clear documentation to support long-term maintenance and collaboration. Recruiting Workflow Knowledge: Strong understanding of recruiter and hiring manager workflows, with the ability to identify operational pain points and develop solutions that balance automation with human judgment. Industry Background: Experience working in an open-source, artificial intelligence, or data science-focused organization is considered a significant advantage. Collaboration and Values: Strong interpersonal skills and a collaborative mindset, demonstrating curiosity, accountability, transparency, empathy, and the confidence to take ownership of challenging initiatives. Inclusive Leadership: A genuine commitment to creating an inclusive working environment where individuals from diverse backgrounds and experiences can thrive. Benefits: Competitive Base Salary: Annual salary ranging from $135,000 to $180,000 USD for US-based team members, depending on location, experience, skills, and qualifications. Annual Bonus: Additional annual performance-based bonus potential. Equity Participation: Opportunity to participate in the company's equity program. Comprehensive Healthcare: Medical, dental, and vision insurance coverage. Disability Coverage: Short-term and long-term disability insurance. Paid Parental Leave: Dedicated leave benefits to support employees and their families. Flexible Vacation: Flexible vacation policy designed to support work-life balance and personal wellbeing. Wellness Support: Monthly wellness stipend to encourage a healthy and balanced lifestyle. Mental Health Resources: Access to an Employee Assistance Program and additional mental health support services. Remote Work: Fully remote working arrangement within the United States, with flexible working hours. Professional Growth: Opportunity to work on innovative AI-powered solutions and contribute directly to the evolution of enterprise data science, machine learning, and artificial intelligence. Collaborative Culture: Join a high-performance, employee-focused environment that values diverse perspectives, open communication, accountability, and professional development.