AI Engineer II, AI Platform
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Job Description
AI Engineer II designing and maintaining AI platform components enabling AI-powered features at MeridianLink. Collaborating with teams to understand integration needs and establish standards.
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
Requirements:
- 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.
Benefits:
- Insurance coverage (medical, dental, vision, life, and disability)
- Flexible paid time off
- Paid holidays
- 401(k) plan with company match
- Remote work
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