Lead AI Engineer

Base Salary Range USD $150,674.69 - USD $195,950.45 /Yr. Job Details Benefits: For information regarding our benefits, please visit: In this role, you will... Be responsible for designing, building, and optimizing scalable AI solutions that support Technology Platforms & Data Modernization. Develop AI engineering components and solution patterns, including retrieval-augmented generation, vector databases, model orchestration, monitoring frameworks, and related platform capabilities. Partner cross-functionally with Technology, Data, Operations, Risk, Security, Compliance, and business stakeholders to evaluate AI use cases, support model and architecture recommendations, and ensure solutions are secure, governed, cost-effective, and aligned to business outcomes. Contribute to AI engineering standards, support complex AI initiatives, and provide technical guidance across teams to drive alignment and successful delivery. Responsibilities and Duties: Serve as a hands‑on subject matter expert for AI engineering capabilities, including AI solution architecture, retrieval-augmented generation, vector databases, model orchestration, model monitoring, and supporting AI infrastructure. Design, build, implement, and optimize scalable AI engineering components, including model context protocol capabilities and related AI integration patterns, retrieval-augmented generation pipelines, vector database solutions, AI application frameworks, model integration patterns, and related platform components. Own hands‑on development and delivery of AI solution patterns, prototypes, production components, and reusable engineering capabilities that support business needs. Configure, integrate, test, deploy, and maintain AI models, tools, APIs, workflows, and platform components to ensure solutions perform reliably in production environments. Evaluate and recommend AI models, tools, and platforms to support business objectives, technical requirements, data needs, risk considerations, and expected operational outcomes. Build, implement, and maintain AI monitoring and control capabilities to track model performance, reliability, drift, usage, business efficacy, cost, and ongoing model viability. Troubleshoot and resolve complex technical issues related to AI solution performance, model integration, data retrieval, orchestration, scalability, cost, reliability, and production support. Create and maintain technical documentation, design artifacts, implementation standards, and operational controls to support transparency, auditability, supportability, and responsible AI governance. Design and implement evaluation approaches for AI solutions, including model performance, retrieval quality, prompt effectiveness, safety, reliability, and business outcome measurement. Optimize AI solutions for business value, scalability, compute usage, operational performance, and cost effectiveness across development, deployment, and production environments. Partner cross‑functionally with Technology, Data, Operations, Risk, Security, Compliance, and business stakeholders to understand business needs, evaluate AI use cases, define solution requirements, and design AI‑enabled process flows that are secure, reliable, compliant, and aligned to intended business outcomes. Contribute to AI engineering standards, solution patterns, and best practices by providing recommendations, technical input, and implementation guidance. Provide technical guidance to engineers, technical peers, and cross‑functional partners by sharing knowledge, offering support, and promoting consistent AI engineering practices. Stay up to date on AI engineering practices, emerging technologies, industry standards, model governance expectations, security requirements, and changes in applicable regulations. Monitor, evaluate, and report on AI solution performance, operational metrics, model health indicators, business outcomes, and Key Performance Indicators as requested. Communicate complex AI, machine learning, data, and technology concepts in clear and understandable terms to technical audiences, business stakeholders, vendors, and governance partners. Perform additional duties as assigned to support evolving business needs. Required Qualifications: Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, Information Systems, or a related field; applicable years of experience may be substituted for a bachelor’s degree. Minimum of eight (8) years of experience in software engineering, AI engineering, machine learning engineering, data engineering, platform engineering, or a related technology discipline, including at least three (3) years of experience designing, developing, deploying, or supporting AI, machine learning, advanced analytics, or intelligent automation solutions in a production or enterprise environment. Experience contributing to complex, cross‑functional technology initiatives, developing technical standards or reusable engineering patterns, and influencing solution design across teams or business functions. Strong coding ability and software engineering foundation, including experience with programming languages such as Python, algorithms, data structures, APIs, systems design, testing, deployment, and modern development practices. Experience with AI/ML concepts and practices, including model development, natural language processing, deep learning, model evaluation, MLOps, model monitoring, or applied AI solution delivery. Experience with AI solution architecture or implementation patterns such as retrieval-augmented generation, vector databases, model orchestration, prompt or context management, AI workflow design, or AI application integration. Experience with cloud, data, or AI platforms such as AWS, Azure, Google Cloud, Databricks, Snowflake, or similar technologies. Working knowledge of responsible AI, model governance, privacy, security, explainability, bias considerations, auditability, and AI risk management practices. Ability to develop strong relationships, influence outcomes, coach others, and partner across the organization. Strong interpersonal skills necessary to communicate professionally and effectively, verbally and in writing, with technology teams, business partners, vendors, governance partners, and company staff. Experience creating customer or business value through continuous improvement, developing practical solutions, supporting complex projects, and delivering successful business outcomes. Ability to articulate complex information in understandable terms to various audiences, including technical recommendations, performance data, risks, and solution options. Strong analytical thinking, problem‑solving ability, and judgment, with the ability to evaluate tradeoffs across model fit, business value, technical complexity, cost, scalability, security, compliance, and operational risk. Demonstrated ability to work independently, influence technical decisions, exercise sound judgment, and provide technical guidance across teams. Preferred Qualifications: Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics, Engineering, or a related technical discipline. Advanced experience with AI/ML engineering, including deep learning, natural language processing, computer vision, model optimization, model design, or applied AI work. Experience with deployment and MLOps tools such as Docker, Kubernetes, MLflow, experiment tracking platforms, CI/CD pipelines, model registries, model monitoring tools, or similar technologies. Experience with agentic AI workflows, AI agents, tool‑using LLM applications, or similar emerging AI solution patterns. Experience developing or applying responsible AI practices, including bias evaluation, explainability, privacy, security, human‑in‑the‑loop controls, model governance, or AI risk management. Experience implementing AI, machine learning, or data solutions in a regulated environment such as financial services, banking, lending, insurance, or another highly governed industry. Experience designing reusable AI platform capabilities, reference architectures, engineering standards, or governance‑aligned implementation patterns for broader organizational adoption. Hours of Work: Full‑time. Work hours will depend on the business hours of the time zone serviced. To the extent permitted by law, the Company may, in its sole discretion, change the work schedule to address business needs. Physical Demands: While performing the duties of this job, the employee is frequently required to sit for extended periods; reach with hands and arms; operate computer and phone systems; and talk or hear. The employee is occasionally required to move about. The employee must occasionally lift and/or move up to twenty (20) pounds. Specific vision abilities required by this job include close vision and the ability to adjust focus. EEO: Mariner Finance is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, creed, sex, gender, gender identity or expression, marital status, age, religion, national origin, sexual orientation, familial or caregiver status, citizenship status, status as a victim of domestic violence, medical condition, genetic information, pregnancy, physical or mental disability, or status as a disabled or Vietnam era veteran. Employee must be able to perform the essential duties/functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential duties/functions of their job, absent undue hardship. Drug/Alcohol/Smoke‑free workplace. This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change or new ones may be assigned at any time or without notice. #J-18808-Ljbffr Mariner Finance