AI Engineer II ( AI Platform)

Summary

MeridianLink is a company focused on delivering AI-powered features through its products. The AI Engineer II role involves designing, developing, testing, and maintaining AI platform components while collaborating closely with product engineering teams to understand their integration needs.

Responsibilities

• 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
• Build observability and monitoring into platform services to track output quality, latency, cost, and system health
• Contribute to design discussions and provide input on trade-offs between simplicity, reliability, and scalability
• Work with product engineering teams to understand how they want to use AI capabilities and translate requirements into platform features
• Participate in technical design sessions and code reviews with product teams building on the AI platform
• Help identify patterns where multiple product teams are solving the same AI integration problem and consolidate that work
• Contribute to documentation, reference implementations, and runbooks that help product teams adopt AI platform services
• Participate in defining and enforcing integration standards — API contracts, error handling patterns, cost attribution
• Mentor junior engineers (Engineer I) and help them grow their understanding of AI systems and platform design
• Implement evaluation and monitoring pipelines that give teams visibility into AI output quality and model behavior
• 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

Skills

• 3–5 years of professional software engineering experience
• Strong proficiency in backend engineering using Python, C#/.NET, Java, or Node.js
• Solid understanding of algorithms, data structures, and system design principles
• Hands-on experience integrating large language models or ML models into production applications
• Working knowledge of retrieval-augmented generation (RAG) concepts, vector databases, and embedding pipelines
• Experience building or contributing to shared services or platform components
• Familiarity with cloud-managed AI services (AWS Bedrock, Azure OpenAI, or equivalent)
• Experience with APIs, asynchronous processing, and event-driven architectures
• Bachelor's degree in Computer Science, Software Engineering, or equivalent professional experience
• Experience with LLM frameworks (LangChain, LlamaIndex, etc.) or prompt engineering
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, or similar)
• Knowledge of containerization and orchestration (Docker, Kubernetes)
• Experience with observability tools and designing monitoring for ML/AI systems
• Prior work in regulated industries with data handling, compliance, or audit requirements
• Experience with fintech, banking, or other financial services environments
• Active daily use of AI-assisted development tools and understanding of their benefits and limitations

Qualifications

Must Haves

• 3–5 years of professional software engineering experience
• Strong proficiency in backend engineering using Python, C#/.NET, Java, or Node.js
• Solid understanding of algorithms, data structures, and system design principles
• Hands-on experience integrating large language models or ML models into production applications
• Working knowledge of retrieval-augmented generation (RAG) concepts, vector databases, and embedding pipelines
• Experience building or contributing to shared services or platform components
• Familiarity with cloud-managed AI services (AWS Bedrock, Azure OpenAI, or equivalent)
• Experience with APIs, asynchronous processing, and event-driven architectures
• Bachelor's degree in Computer Science, Software Engineering, or equivalent professional experience

Nice to Haves

• Experience with LLM frameworks (LangChain, LlamaIndex, etc.) or prompt engineering
• Familiarity with vector databases (Pinecone, Weaviate, Milvus, or similar)
• Knowledge of containerization and orchestration (Docker, Kubernetes)
• Experience with observability tools and designing monitoring for ML/AI systems
• Prior work in regulated industries with data handling, compliance, or audit requirements
• Experience with fintech, banking, or other financial services environments
• Active daily use of AI-assisted development tools and understanding of their benefits and limitations

Benefits

• As a fully remote company, we're intentional about creating meaningful opportunities to connect with your team.
• You'll have access to AI/ML training, job-specific technical development, monthly soft-skill sessions, and mentorship from experienced Senior and Staff engineers.
• Work-Life Balance: We understand that you have a full life outside work. We honor your personal commitments while maintaining productivity.
• MeridianLink is certified as a Great Place to Work® for 2026.