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

Compensation Range: $160K - $180K