Job description

Location: Hybrid- Employees are required to work 3 days out of the nearest office location. Aravo Solutions, Inc., provides leading third-party risk management (TPRM), ESG, and vendor lifecycle management solutions powered by intelligent automation software and designed to meet the needs of TPRM teams at Global 2000 enterprises. At Aravo, we believe that in an increasingly interconnected world, managing risk is a critical pillar of global resilience. Traditional, manual approaches to TPRM can no longer keep pace with today’s scale and speed of disruption. That’s why we have pioneered an Intelligence-First™ approach. 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. We are fundamentally redesigning how organizations see, understand, and act on risk by embedding AI directly into the core of their workflows. Joining Aravo means working at the forefront of AI in TPRM and collaborating with a team that views AI as a partner, not a replacement. 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! Position Overview: We are seeking a highly skilled Senior Software Engineer to help design and build our AI agent platform — including autonomous agents that process data, retrieval-augmented generation (RAG) systems, and infrastructure for deploying models in production. This role is critical to expanding our platform's AI capabilities, enabling agents to map outputs onto structured data models, and scaling GPU-based model deployment. You will work closely with Product Management, DevOps, and other engineering teams to align technical decisions with business goals while delivering progressively more capable and high-performing AI/agent functionality. This role requires strong experience across both backend systems engineering and applied AI/ML, with a significant focus on production-grade agent tooling and retrieval-based systems. Requirements Key Responsibilities: · Collaborate closely with Product Management to translate complex business and technical concepts into actionable deliverables for a multi-tenant, cloud-native AI platform · Design and extend tooling that maps AI outputs onto structured, customer-specific data models · Build and evolve RAG pipelines for document parsing and question answering · Develop and maintain multiple agent types (e.g., classification, document parsing, custom workflows), including authentication, error handling, and observability · Design for scale, supporting high availability, multi-tenancy, and rapid growth · Deploy and operate ML models on GPU infrastructure in production · Ensure integrations meet security, compliance, and performance requirements · Provide technical leadership through design reviews, code reviews, and mentorship of other engineers Qualifications: Required · Bachelor's in Computer Science, Engineering, or equivalent experience in a related field · 7+ years of software engineering experience, with a strong focus on Java-based systems · Proficiency in Python, including AI/ML libraries and PDF extraction · Deep understanding of NLP, neural networks, and LLMs, with the ability to implement concepts from technical research papers · Extensive experience building and consuming RESTful APIs · Strong data architecture skills, including database design, data modeling, and schema management with relational and non-relational databases · Use of AI technologies in production systems · Excellent communication, organizational, and interpersonal skills · Agile/Scrum or other iterative methodology experience Preferred Qualifications/Skills/Soft Skills: · Adept at designing solutions in public, private, and hybrid infrastructure models · Knowledge of AI infrastructure, LLM APIs, and experience with Model Context Protocol (MCP) or similar AI agent frameworks · Experience deploying ML models to GPUs in production environments · Experience with enterprise integrations or third-party/vendor systems · Familiarity with API gateways and security standards (OAuth, JWT) · Comfortable in Unix/Linux scripting environments Why Join Us: At Aravo Solutions, Inc., we offer a dynamic and inclusive work environment where employees are encouraged to innovate, grow, and make a meaningful impact. We provide competitive compensation and benefits packages, opportunities for professional development, and the chance to work alongside industry experts on cutting-edge projects. Benefits · 100% Employer Paid Medical Insurance options for the Employee and Family · Paid Maternity and Paternity Leave · Life and AD&D Insurance · Long-Term Disability Insurance · 401K with Company Matching · Equity Participation · 4 Weeks of Vacation · Fully Stocked Kitchens · Company-Sponsored Charitable Day of Giving Events As a SaaS company, we're all about smart technology and forward-thinking innovation. But when it comes to building our team, we're firm believers that people should evaluate people. That’s why we’ve intentionally turned off the AI-driven screening and scoring features in our Applicant Tracking System (ATS). When you apply to Aravo, your application isn't filtered out by an invisible algorithm—it's reviewed by a real recruiter working hand-in-hand with our hiring managers. We've also established and enforced a companywide policy governing the appropriate use of AI, including how it can enhance the hiring process for managers without relying on an invisible, unknown entity to make decisions. If you're taking the time to learn about us and put your best foot forward, we're committed to matching that effort with ours. Technology might power our platforms, but when it comes to recognizing potential, real people will always remain at the heart of our hiring decisions. Aravo Solutions Inc. is registered as an employer in many, but not all, states. If an applicant is not in or able to work from a state where Aravo Solutions Inc. is registered, they may not be eligible for employment. The eligible states include: FL, GA, MA, MO, NC, NH, NV, OR, PA, SC, TN, and TX.

Requirements

Must-haves

Location: Hybrid- Employees are required to work 3 days out of the nearest office location.
You will work closely with Product Management, DevOps, and other engineering teams to align technical decisions with business goals while delivering progressively more capable and high-performing AI/agent functionality.
Collaborate closely with Product Management to translate complex business and technical concepts into actionable deliverables for a multi-tenant, cloud-native AI platform
Design and extend tooling that maps AI outputs onto structured, customer-specific data models
Build and evolve RAG pipelines for document parsing and question answering
Develop and maintain multiple agent types (e.g., classification, document parsing, custom workflows), including authentication, error handling, and observability
Design for scale, supporting high availability, multi-tenancy, and rapid growth
Deploy and operate ML models on GPU infrastructure in production
Ensure integrations meet security, compliance, and performance requirements
Provide technical leadership through design reviews, code reviews, and mentorship of other engineers
Bachelor's in Computer Science, Engineering, or equivalent experience in a related field
7+ years of software engineering experience, with a strong focus on Java-based systems
Proficiency in Python, including AI/ML libraries and PDF extraction
Deep understanding of NLP, neural networks, and LLMs, with the ability to implement concepts from technical research papers
Extensive experience building and consuming RESTful APIs
Strong data architecture skills, including database design, data modeling, and schema management with relational and non-relational databases
Use of AI technologies in production systems
Excellent communication, organizational, and interpersonal skills
Agile/Scrum or other iterative methodology experience
Adept at designing solutions in public, private, and hybrid infrastructure models
Knowledge of AI infrastructure, LLM APIs, and experience with Model Context Protocol (MCP) or similar AI agent frameworks
Experience deploying ML models to GPUs in production environments
Experience with enterprise integrations or third-party/vendor systems
Familiarity with API gateways and security standards (OAuth, JWT)

Nice-to-haves

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aimljavapythonagilescrumllmapi

Platform: workable
Effort: medium

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401k

Professional Development