Software Engineer- AI Platform

We are seeking a Software Engineer to serve as a foundational contributor to our next generation unified AI platform, designed to power all current and future products across the organization. This role is highly impactful and hands-on, focused on greenfield development, deep systems integration, and building AI agents that operate across complex enterprise workflows.

You will play a key role in designing, building, and scaling LLM-powered agent systems integrated through Model Context Protocol (MCP) interfaces, enabling intelligent automation, secure data access, and retrieval-augmented generation (RAG) capabilities across a large, mission-critical SaaS platform.

Our environment supports a debt collection workflow / ERP SaaS solution, where robustness, security, correctness, and auditability are essential. The core platform is primarily Java-based, and the AI platform must integrate cleanly with existing systems while setting a strong architectural foundation for the future.

• Build components of Finvi's unified AI platform that serve multiple products and business functions
• Contribute to greenfield development of AI-driven systems within architectural direction set by senior engineers
• Implement LLM and MCP-based integrations for consistent context handling and tool invocation
• Partner with platform, backend, and product teams to integrate AI capabilities into Finvi's existing systems

• Build LLM-powered features that operate across enterprise workflows, data sources, and tools
• Build and evolve RAG pipelines, including embedding strategies, vector search, and indexing across many internal and external data sources
• Optimize prompt engineering, orchestration logic, and agent memory/context strategies for accuracy and reliability
• Evaluate and integrate LLMs and AI tooling with a focus on performance, cost, and enterprise suitability

• Build systems that meet high standards of security, robustness, and reliability
• Build AI solutions that are traceable, well-logged, resilient to failure and edge cases, and safe for use in a regulated debt-collection environment
• Collaborate with security and compliance teams to ensure adherence to applicable regulations and data-handling requirements

• Contribute to best practices in AI engineering, testing, monitoring, and deployment
• Partner closely with product managers and stakeholders to translate business problems into AI-driven solutions
• Contribute to the AI team's roadmap and platform direction as priorities evolve

• 36 years of professional software engineering experience, with a backend or platform focus
• Strong experience building production systems in Java (core language of the platform)
• Hands-on experience working with LLMs, including prompt engineering, orchestration, and evaluation
• Experience building systems that integrate with multiple data sources and search targets
• Solid understanding of distributed systems, APIs, data pipelines, and system reliability
• Strong engineering fundamentals: testing, observability, performance tuning, and secure coding
• Communicates clearly and effectively across technical and non-technical stakeholders, including platform, product, and security partners
• Demonstrates a practical, execution-oriented learning style, quickly applying new concepts to real production use cases
• Adapts approach based on feedback, failures, and evolving priorities while maintaining momentum
• Holds a high bar for engineering quality, especially given the business-critical and regulated nature of the platform

• Experience designing or implementing RAG architectures or pipelines
• Experience building or integrating AI agents or autonomous/semi-autonomous systems
• Familiarity with Model Context Protocol (MCP) or similar agent/tool interface standards
• Experience with vector databases, embeddings, and large-scale search/indexing systems
• Exposure to regulated or compliance-heavy domains (Fin Tech, healthcare, legal, debt collection, etc.)
• Experience deploying AI systems in enterprise SaaS environments
• Hands-on experience with AWS, Azure, GCP, or OCI

• You will help define the AI backbone of a company-wide platform used by hundreds of internal users and customers
• Your work will directly influence the reliability, scalability, and innovation of all AI-driven features
• You will have real ownership over technical, architectural, and strategic aspects of core systems
• This is not an experimentation role; it’s production, platform-level AI engineering with real impact
• Opportunity to build foundational AI infrastructure from the ground up
• A role at the intersection of AI, platform engineering, and enterprise SaaS
• A collaborative culture with real ownership and autonomy

• Self-starting mentality with the ability to identify problems, propose solutions, and move initiatives forward without waiting for direction
• Strong bias for action and execution, with a track…