Staff Software Engineer, AI

🕒 April 22

🇺🇸 United States – Remote

💵 $152.5k - $260k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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MeridianLink

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1998

💳 Fintech

🏦 Banking

☁️ SaaS

💰 $485M Post-IPO Debt on 2021-11

Fintech • Banking • SaaS

MeridianLink is a leading provider of SaaS solutions for financial institutions, specializing in loan origination systems and digital transformation technologies. Their end-to-end platform enhances digital experiences through integration with mortgage LOS, deposit account opening solutions, and more. MeridianLink's cloud-based systems improve efficiency in loan processing and collections, data-driven decision-making, and account management. The company collaborates with partners to expand market reach and drive growth in the fintech industry. With over 25 years of experience, MeridianLink is dedicated to supporting banks, credit unions, and other financial service providers through technology and business intelligence.

📋 Description

• Own the reference architecture for the AI platform, encompassing API abstractions, prompt and version management, RAG infrastructure, vector retrieval, evaluation harnesses, and model serving. • Lead build-vs-buy evaluations for AI components, including due diligence and integration planning. • Design foundational data pipelines and infrastructure to support reliable, scalable AI services. • Define and document API contracts, standards, and platform interfaces across engineering. • Contribute to backend development in Python and RESTful API design, including integrations with leading AI providers. • Participate in full-stack delivery when needed, using React/TypeScript/Vite to deliver AI features. • Build and maintain tooling, SDKs, and platform APIs to enable safe, scalable AI adoption by product teams. • Drive improvements to AI-assisted development workflows with tools like GitHub Copilot and Claude. • Implement integrations with LLMs: context management, prompt templating, response validation, and robust fallback strategies. • Build and maintain evaluation frameworks for reproducible model testing. • Establish observability and performance tracking for AI services. • Participate in designing vector-based retrieval and model serving infrastructure as custom model capabilities become a focus. • Advise and collaborate with Security through architecture and design phases, ensuring compliance and security standards are met. • Apply secure-by-default principles (encryption, least privilege, audit logging) and stay current with financial data governance and privacy standards. • Collaborate with Product to translate business needs into technical designs and specifications, while contributing a strong architectural perspective. • Support AI platform roadmap development with product leadership. • Engage in companywide architectural forums and workgroups to drive engineering standards. • Partner with Data Engineering, DevOps/SRE, and Security to ensure aligned technical foundations. • Mentor L3–L4 engineers through code reviews, design sessions, and architectural guidance. • Promote engineering excellence, robust documentation, and reusable internal resources.

🎯 Requirements

• 8+ years in professional software engineering, with demonstrated cross-team architectural influence • Proven end-to-end delivery of AI-powered features, from product concepts to production • Experience leading large, complex technical initiatives • Strong proficiency in Python and RESTful API development (FastAPI, Django) • Knowledge of full-stack development (React, TypeScript) • Hands-on integration with third-party LLM/AI APIs • Experience with AWS (preferred), including IAM, networking, managed services, and storage • Solid foundation in distributed systems, API design, cloud-native architecture • Comfortable with CI/CD pipelines, version control, Docker, and AI-assisted development tools • Demonstrated ability to author durable technical proposals (RFCs, ADRs) • Clear communicator with technical and non-technical stakeholders • GenAI experience (e.g., RAG pipelines, prompt management, LLM evaluation, agent frameworks) • Familiarity with vector databases/semantic search (Pinecone, pgvector, OpenSearch) • Exposure to model serving, MLOps/LLMOps practices, and model lifecycle/deployment tools • Experience building developer platforms, SDKs, and self-service engineering tooling • Experience with IaC tools (Terraform/Pulumi), Kubernetes, and observability tools (Prometheus, Grafana, Datadog) • Leadership in technical communities, mentoring, and architectural standards • Bachelor’s in Computer Science, Software Engineering, or equivalent experience

🏖️ Benefits

• Insurance coverage (medical, dental, vision, life, and disability) • Flexible paid time off • Paid holidays • 401(k) plan with company match • Remote work