Agent Builder- AI​/SaaS- Entry Level

Location: Hybrid – employees may be required to work out of the nearest office location for quarterly meetings 1‑4 times annually.

Aravo Solutions, Inc. provides leading third‑party risk management (TPRM), ESG, and vendor lifecycle management solutions powered by intelligent automation software. Designed to meet the needs of TPRM teams at Global 2000 enterprises, our innovative Intelligence First™ Platform uses AI to optimize time‑intensive processes, reduce manual work, and drive better business outcomes. Trusted by millions of third‑party users in 195+ countries, Aravo provides guidance for the most complex third‑party networks in the world, helping them mitigate risk, build business resilience, and protect their reputations.

Join us at Aravo Solutions, where we are passionate about helping companies manage risk and promote integrity across their extended enterprise. You will have the opportunity to work alongside industry experts, leverage the latest technologies, and contribute to shaping the future of third‑party risk management.

As a member of the Agent Builder team, you will assist in the design, configuration, and deployment of intelligent AI agents that enhance Aravo's SaaS‑based Third‑Party Risk Management (TPRM) platform. This role bridges no‑code/low‑code AI engineering, solution configuration, and customer enablement, ensuring our clients can maximize value from AI‑driven automation within a configurable, enterprise‑grade risk management solution.

You will perform high‑level design and implementation based on both internal and external specifications for product requirements, architecting scalable AI‑driven Agent Solutions. In this capacity, you will evaluate and identify opportunities for expanded user value creation, creatively design and build complex AI Agents, iterate and resolve complex bugs, and deliver high‑quality AI‑enabled capabilities tailored to company‑identified and client‑specific use cases. This role collaborates closely with product management, data science, customer success, and deployment teams to ensure seamless integration and adoption of AI features across the product suite.

You will also review and execute unit, integration, and regression test plans to ensure consistency, reliability, and performance of AI‑enhanced functionality. Our ideal candidate will have exceptional communication and problem‑solving skills, with the ability to thrive in a fast‑paced, collaborative environment.

• AI Agent Design & Development
  • Design, build, test and document AI agents that automate workflows, enhance analytics, and support risk/compliance decision‑making in the TPRM domain
  • Develop and customize AI Agent “blueprints” to map business logic, using LLM‑powered and rules‑based components for task automation and decision‑making
  • Build and test agent interfaces, ensuring seamless interaction in user‑facing contexts (AI canvas, dashboards, embedded widgets)
• Configurability & Solution Management
  • Implement no‑code/low‑code configuration frameworks enabling customers to adapt AI behaviors to their business processes
  • Ensure AI agents integrate seamlessly with existing SaaS workflows, APIs, and risk scoring engines
  • Configure conversational flows, prompt logic, and integrations with internal and external APIs, business systems, and third‑party data providers
  • Conduct QA and testing to identify issues in intent recognition, response accuracy, and workflow automation
• Governance & Continuous Improvement
  • Produce clear documentation of agent logic, underlying configuration, prompt strategies, escalation paths and identified performance metric tracking
  • Collaborate cross‑functionally to serve as a bridge between business users (who help prototype and refine workflows) and development teams (who implement integrations and advanced logic)
  • Assist in identifying and implementing guardrails, supporting data integrations, and escalation logic for complex or off‑topic use cases to transfer to human agents when necessary
  • Maintain, troubleshoot, and analyze existing agents, using visual logs, traces, and analytical tools to improve workflow reliability and effectiveness