AI Engineer II ( AI Platform)

About the role

You will design, develop, test, and maintain core AI platform components that power consistent and reliable AI features across MeridianLink products. You will own the implementation of model integration layers, retrieval-augmented generation infrastructure, prompt management systems, and evaluation pipelines that serve as the foundation for product teams. This role requires close collaboration with Senior and Staff engineers on architecture while directly partnering with product engineering teams to translate AI integration needs into platform capabilities. You will help define and enforce standards and patterns that teams follow when building on top of the AI platform. The role emphasizes building observable, cost-aware, and safe AI services within a regulated financial services context. You will mentor junior engineers and contribute to the foundational systems that enable scalable AI adoption.

Key facts

What you'll do

• Implement AI platform components including model serving layers, retrieval infrastructure, prompt management, and output evaluation services under the guidance of Senior and Staff engineers
• Develop and maintain APIs that product teams use to integrate AI capabilities into their applications with clear contracts and predictable behavior
• Build observability and monitoring into platform services to track output quality, latency, cost, and system health in production environments
• Contribute to design discussions and provide input on trade-offs between simplicity, reliability, and scalability for platform features
• Work with product engineering teams to understand how they want to use AI capabilities and translate those requirements into robust platform features
• Participate in technical design sessions and code reviews with product teams building on the AI platform to ensure alignment with standards
• Help identify patterns where multiple product teams are solving the same AI integration problem and consolidate that work into shared platform services
• Contribute to documentation, reference implementations, and runbooks that help product teams adopt AI platform services safely and efficiently
• Participate in defining and enforcing integration standards including API contracts, error handling patterns, and cost attribution for AI services
• Mentor junior engineers (Engineer I) and help them grow their understanding of AI systems and platform design principles
• Implement evaluation and monitoring pipelines that give teams visibility into AI output quality, model behavior, and performance regressions over time
• Contribute to content safety standards and compliance guardrails appropriate for a regulated financial services environment
• Help design systems that properly handle PII, maintain audit trails, and meet data residency requirements in AI pipelines
• Support the operational readiness of AI platform services through runbooks, alerting strategies, and incident response practices

Requirements

• 3-5 years of professional software engineering experience with a track record of delivering production-grade software
• Strong proficiency in backend engineering using Python, C#/.NET, Java, or Node.js to implement reliable services
• Solid understanding of algorithms, data structures, and system design principles applied to scalable platforms
• Hands-on experience integrating large language models or ML models into production applications in real-world scenarios
• Working knowledge of retrieval-augmented generation (RAG) concepts, vector databases, and embedding pipelines used in AI applications
• Experience building or contributing to shared services or platform components that are consumed by multiple teams
• Familiarity with cloud-managed AI services such as AWS Bedrock, Azure OpenAI, or equivalent offerings in regulated environments
• Experience with APIs, asynchronous processing, and event-driven architectures to build responsive platform services
• Bachelor's degree in Computer Science, Software Engineering, or equivalent professional experience demonstrating technical depth
• Ability to read, interpret, and implement detailed technical requirements without ambiguity
• Willingness to work within established security, compliance, and data governance policies relevant to financial services
• Commitment to writing clean, maintainable, and well-tested code that can be reviewed and understood by peers
• Capacity to communicate technical trade-offs clearly to both engineering and non-engineering stakeholders
• Reliability in meeting deadlines and delivering incremental value that aligns with product and platform roadmaps

Nice to have

• Experience with LLM frameworks such as LangChain or LlamaIndex and practical prompt engineering techniques
• Familiarity with vector databases like Pinecone, Weaviate, or Milvus and optimization strategies for similarity search
• Knowledge of containerization and orchestration tools including Docker and Kubernetes for deploying AI services
• Experience with observability tools and designing monitoring for ML/AI systems including metrics and tracing
• Prior work in regulated industries with strict data handling, compliance, or audit requirements
• Experience with fintech, banking, or other financial services environments and their risk and compliance constraints
• Active daily use of AI-assisted development tools and an understanding of their benefits, limitations, and integration patterns

Practical notes

This role is full-time and remote within the United States. The position requires adherence to corporate security, compliance, and data governance policies. Travel is not required, and no visa sponsorship is provided at this time.