PactFi

Compensation

Full Description

About PactFi Private asset markets (PE, Private Credit, VC, Real Estate) have 10x to 9.8T in AUM over the past decade and are projected to grow to $17T in the next five years. However, digital infrastructure has not kept pace, with most of the market operating predominantly in error-prone, internal-only software solutions. PactFi provides secure, end-to-end, operational infrastructure for managing complex private credit transactions. Our web-based application brings together all parties involved in such a transaction to more efficiently allocate capital, complete KYC, share documents, manage funds flow, and more. The platform is secured to a bank-grade standard, and we have received our SOC 2 Type 2 attestation. PactFi was developed in close partnership with two of the industry's largest players, both of whom represent the top 3 players in the private credit space by both size (AUM) and deal activity. Key Responsibilities AI Architecture & Implementation Identify high-value AI opportunities and design scalable solution - such as LLM workflows, intelligent agents, and decision-support systems - that integrate seamlessly with PactFi’s platform. Develop architectural patterns, best practices, and reusable AI frameworks to accelerate adoption across engineering teams. Ensure AI solutions align with PactFi’s product roadmap, data strategy, security standards, and regulatory obligations. Cross-Functional Collaboration Work closely with engineering, product, and business stakeholders to understand requirements and translate them into technically sound AI solutions. Provide technical guidance on model capabilities, limitations, feasibility, and appropriate use cases. Collaborate with data engineering teams to ensure proper access to high-quality data pipelines, feature stores, and model-serving infrastructure. AI/ML Model Integration & Evaluation Evaluate and integrate advanced AI models and platforms, including AWS Bedrock, Azure AI, Google Gemini, OpenAI, and others. Lead the design and implementation of workflows for model orchestration, fine-tuning, retrieval-augmented generation (RAG), and inference. Assess tools, frameworks, and model providers to recommend solutions based on performance, security, cost, and business alignment. Prototype, test, and validate new AI capabilities before scaling to production environments. Platform & Systems Architecture Architect AI services and components using modern cloud-native patterns, microservices, and enterprise integration approaches. Work with engineering teams to ensure AI-enabled features are scalable, observable, secure, and maintainable. Define standards for logging, monitoring, lifecycle management, and continuous improvement of AI systems. Qualifications Required Proven experience designing and delivering successful architectural solutions that incorporate AI including LLMs, NLP Pipelines, vector databases, and model orchestration in practical, impactful ways. Deep understanding of modern technology stacks, including AI/ML platforms, cloud computing (AWS, Azure, GCP), microservices, and enterprise integration patterns. Strong technical proficiency with AI/ML technologies, including: LLMs and agent frameworks Vector databases and embeddings Model orchestration and fine-tuning NLP/NLU pipelines and predictive modeling Ability to evaluate trade-offs and make informed architectural decisions balancing performance, cost, and business value. Experience in financial services, capital markets, or telecommunications is highly desirable. Excellent communication and collaboration skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders. Strong problem-solving skills and the ability to convert ambiguous business needs into well-defined AI solutions. What We Offer Competitive salary + equity. Healthcare coverage. 401k