InvoiceCloud, Inc.

Customer Success Manager

• Builds strong, strategic partnerships with a defined group of clients
• Ensures clients achieve maximum value from the InvoiceCloud platform
• Guides day-to-day engagement, strengthens retention, and influences digital adoption programs
• Identifies opportunities for product expansion
• Executes strategies that increase digital payment adoption and improve customer experience

Security Engineer

• Leads AI Security Architecture & Secure Design initiatives by designing and implementing lifecycle security controls across data ingestion, training, evaluation, deployment, and monitoring environments to measurably reduce AI-specific risk while maintaining product velocity.
• Conducts structured Threat Modeling & Risk Assessment exercises for generative AI, RAG, and agent-based systems, evaluating risks such as prompt injection, data poisoning, model extraction, model inversion, abuse/misuse, and data leakage, and mapping findings to OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF to drive remediation through engineering teams.
• Defines and operationalizes Monitoring, Detection & Incident Response capabilities for AI systems by implementing prompt and output telemetry, tool-call logging, anomaly detection, and AI-specific incident response playbooks integrated into SIEM/SOC workflows.
• Delivers measurable outcomes aligned to 30-, 150-, and 210-day milestones, including secure reference architectures, hardened AI environments, integrated security controls, and executive-ready reporting on AI risk reduction and posture maturity.
• Establishes and formalizes AI Governance, Privacy & Third-Party Risk requirements by defining security expectations for AI use cases, third-party models, vendor integrations, and sensitive data usage, embedding controls into SDLC, procurement, and engineering standards.
• Drives Cross-Functional Collaboration & Enablement by partnering with Engineering, Data Science, DevSecOps, Product, Legal/Privacy, and SOC teams to align on risk appetite, escalation paths, and secure design guardrails while raising AI security maturity across the organization.
• Inventories current and planned AI/ML initiatives, documents system architectures and sensitive-data touchpoints, and implements a structured AI security intake and risk-rating process that ensures accountability and transparency.
• Develops and communicates forward-looking 6- and 12-month AI security maturation plans that align technical priorities with business goals and clearly articulate risk trends, metrics, and investment needs to Security leadership and the CISO.
• Integrates Secure MLOps / MLSecOps controls into AI delivery pipelines, including secure model registries, artifact signing and provenance validation, dependency scanning, secrets management, CI/CD guardrails, and hardened training and inference environments across AWS and Azure.
• Builds and scales AI Security Testing & Red Teaming workflows by creating repeatable adversarial evaluation plans for jailbreaks, model evasion, prompt injection, and data exfiltration scenarios, ensuring security controls remain effective over time.
• Develops automated regression test harnesses to continuously validate AI security protections as models, prompts, and dependencies evolve, reducing manual effort and improving coverage.
• Establishes a sustainable AI security operating rhythm that includes intake reviews, threat modeling checkpoints, remediation tracking, and structured monitoring ownership to bring consistency and order to AI risk management.
• Advances AI Security Testing & Red Teaming capabilities through adversarial experimentation and multi-dimensional analysis, proactively identifying emerging AI threat patterns before production impact.
• Leverages AI and automation to strengthen testing coverage, automate regression validation, enhance anomaly detection logic, and improve the scalability of AI security monitoring and response.
• Continuously evaluates emerging AI security research, tooling advancements, and regulatory developments, translating insights into adaptive defensive controls that support InvoiceCloud’s AI-first strategy while enabling responsible innovation.

AI Security Engineer

Cloud Engineer

• Support the design, deployment, and operation of Azure-native infrastructure powering InvoiceCloud’s enterprise SaaS platform.
• Contribute to the maintenance and improvement of Azure Kubernetes Service (AKS) clusters and supporting services.
• Assist with infrastructure as code (IaC) implementations using Terraform.
• Support Azure networking and security configurations under the guidance of senior engineers.
• Collaborate closely with application teams running Windows/IIS and .NET workloads.
• Assist with CI/CD pipeline enhancements.
• Help maintain monitoring and alerting systems using Azure Monitor and Log Analytics.
• Participate in incident response and post-incident reviews.

Associate Cloud Platform Engineer – Azure, Kubernetes

Data Analyst

• Own annual participation in compensation surveys (Radford/Mercer), including job matching, data submission, and results analysis.
• Conduct job pricing and market benchmarking for new and existing roles, providing data-driven recommendations to support hiring and internal equity decisions.
• Support annual merit and bonus cycle administration: data preparation, Workday configuration, manager communications, and results reporting.
• Maintain and evolve InvoiceCloud's job architecture, including job families, levels, and grade structure in Workday.
• Respond to ad hoc compensation questions from HRBPs, Talent Acquisition, and managers, providing market context and consistent guidance.
• Support pay equity analysis and contribute to proactive identification of internal equity concerns.
• Assist with preparation of compensation materials for the Board of Directors and ELT, including benchmarking summaries and total rewards overviews.
• Build and maintain People dashboards and recurring reports covering headcount, attrition, promotions, LOA, and contractor data.
• Own the Board and Executive team reporting cycles, ensuring data accuracy, consistent metric definitions, and on-time delivery.
• Develop AI-assisted documentation and calculation tools that reduce manual rework and improve transparency in executive reporting workflows.
• Partner with HRIS and People Ops to ensure data integrity across Workday and downstream reporting systems.
• Identify and pursue opportunities to automate or streamline reporting processes using available tools and technology.
• Support compensation alignment for InvoiceCloud's India team, including local market benchmarking and coordination with global HR counterparts.

Customer Success Manager

AI Security Engineer

Associate Cloud Platform Engineer – Azure, Kubernetes

Compensation & Analytics Analyst