You will design, develop, and maintain AI platform components such as model serving layers, retrieval infrastructure, and evaluation pipelines. You will also collaborate with product engineering teams to integrate AI capabilities while establishing standards for reliability, safety, and compliance.
MeridianLink
23 Remote Job Openings at MeridianLink
Acts as the first line of defense in resolving client inquiries and documenting interactions in case management systems. Coordinates with internal departments to ensure issues are resolved and mentors Level 1 associates.
Leads the end-to-end delivery of consumer implementations from kickoff through go-live, managing timelines and customer accountability. Coordinates with Implementation Analysts and reports project status and risks to the Services Manager.
Drive the end-to-end delivery of complex AI/ML initiatives and the AI-Driven SDLC (AIDLC) across engineering, product, and data teams. Establish team processes, facilitate agile ceremonies, and manage project plans to ensure high-quality outcomes for agentic platforms.
Lead the technical execution and coordination of an agile engineering team while remaining hands-on with coding and architecture. Partner with Product and QA teams to execute roadmaps and improve operational reliability and engineering standards.
Lead the technical documentation strategy and manage a team of writers to create comprehensive guides for a lending platform. This includes designing content structures, managing authoring tools, and partnering with product and engineering teams to align documentation with release cycles.
The Implementation Analyst manages the end-to-end lifecycle of client software deployments to ensure successful launches and long-term adoption. They act as a trusted advisor, coordinating between clients and internal departments to resolve challenges and optimize platform utilization.
Design, build, and maintain scalable data pipelines and products to ensure high-quality data delivery across the organization. Collaborate with cross-functional stakeholders to implement data models and optimize batch and real-time ingestion processes.
Staff Platform Engineer - Platform Integrations
MeridianLink
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Full Time
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2 months ago
MeridianLink
The Staff Platform Engineer serves as the primary technical authority for integration architecture and API design across multiple product lines. They are responsible for defining standards, leading technical due diligence, and building shared integration infrastructure to connect internal and external systems.
Build and maintain shared CI/CD infrastructure, AI development tooling, and sandbox environments to improve engineering productivity. Drive the adoption of AI-native development pipelines and agent infrastructure across R&D teams.
Oversees the full employee lifecycle and manages employee relations programs to ensure legal compliance and systematic resolution of concerns. Acts as a strategic partner to management while designing and implementing HR projects and policies.
Build and maintain foundational systems for identity, authentication, and authorization across a multi-product SaaS platform. Implement backend service integrations and leverage AI-assisted workflows to accelerate software design and delivery.
Lead the technical execution and coordination of an agile engineering team while remaining hands-on with coding and architecture. Focus on mentoring engineers, improving delivery practices, and partnering with Product and QA to execute the roadmap.
The UX Designer will create intuitive, scalable digital experiences for B2B enterprise users in the financial services and lending space. This includes managing the full design lifecycle from discovery and prototyping to final specifications and implementation within a design system.
Design and optimize user experiences for digital financial products, specifically focusing on online loan and bank account applications. Collaborate with cross-functional teams to implement AI-assisted design workflows and scalable design systems.
Lead the strategy and delivery of AI-powered automation capabilities within a vertical SaaS platform for financial services. Translate complex lending workflows into scalable product experiences while collaborating with engineering, data science, and compliance teams.
The role involves designing, developing, and maintaining scalable software solutions and product features in a cloud-based environment. Responsibilities include collaborating on technical architecture and contributing to CI/CD pipelines and operational reliability.
Lead the design and delivery of predictive solutions such as automated underwriting and risk scoring for financial institutions. Manage complex datasets to build, test, and deploy machine learning models that optimize lending operations.
Design and build curated data structures, including vector stores, feature stores, and graph databases, to support AI and ML applications. Lead data discovery efforts to identify trends in lending and account-opening data to inform business and AI use cases.
The Principal Data Architect will design and implement the end-to-end enterprise data architecture, including conceptual, logical, and physical models. They will lead the lakehouse strategy on Azure Databricks and establish standards for data integration, governance, and lineage.
The Senior Director will lead the rollout of a new pricing and packaging program while establishing repeatable processes for ongoing pricing optimization. They will collaborate across departments to manage annual price updates, competitive intelligence, and monetization frameworks for new product features.
The Staff Software Engineer will design and build foundational AI infrastructure to support scalable, customer-facing AI capabilities across credit union software products. They will lead architectural strategy, mentor engineering teams, and ensure production-grade AI systems meet financial compliance and security standards.
The Product Manager will oversee the product roadmap, pricing, and go-to-market strategy while acting as a liaison between business requirements and engineering. They are responsible for maximizing development team output within a scrum framework and analyzing market data to identify new product opportunities.