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.