AI Engineer II, AI Platform at MeridianLink

Role overview

This AI Engineer II is a mid-level engineering role responsible for designing, developing, testing, and maintaining AI platform components that enable MeridianLink's products to deliver AI-powered features consistently and reliably. You will work within the AI platform team to implement services such as model integration layers, retrieval-augmented generation infrastructure, prompt management systems, and evaluation pipelines. This role collaborates closely with Senior and Staff engineers on architecture, works directly with product engineering teams to understand their AI integration needs, and helps establish the standards and patterns teams follow when building on top of the AI platform.

Responsibilities

• Design, build and operate software or platform systems for AI platform engineering.
• Collaborate with product, engineering and customer stakeholders.
• Improve reliability, performance, testing, automation and documentation.
• Translate complex requirements into maintainable production systems.

Qualifications

• 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

Technology in this role

• Python: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• Java: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• C#: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• .NET: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• Node.js: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• AWS: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• Azure: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• Kubernetes: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• Docker: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• SQL: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• C: Python Java C# .NET Node.js AWS Azure Kubernetes Docker .
• LLM: 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 .
• large language models: 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 .
• RAG: 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 .
• LangChain: 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 .
• Git: • Experience with version control (Git) and CI/CD .

Benefits

• Location and remote arrangement as stated in the official posting.
• Opportunity to work on mapping, financial technology or AI platform products.

About MeridianLink

This is a deeply technical, hands-on engineering role and an integral part of the platform itself. You will write the code that traces agent actions across a multi-agent workflow, adopt and extend leading open-source explainability and observability frameworks, and build the primitives product teams use to surface explanations to lenders, credit unions, and their borrowers. You should have real hands-on experience with LLM-based systems and a strong pull toward the problems of trust, tracing, and evaluation. You do not need to be an expert in all of it. This is a place to build that expertise while the platform is being built, working alongside a Staff engineer team lead and architects who will invest in your growth.

What it means to be an L2 AI Engineer at MeridianLink

L2 AI Engineers handle a broad range of work independently, from bug fixes to feature development. They have developed a specialization and are deepening it. They write code that other engineers trust, ask good questions, and are starting to help the engineers around them. L2 AI Engineers at MeridianLink are active, daily users of AI-assisted development tools.

Completes assigned features and bug fixes independently, with limited need for day-to-day guidance

Designs components within a well-defined scope; escalates questions on complex system design rather than guessing

Participates in code review and provides constructive feedback

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