Principal Machine Learning

OverviewGeneral PurposeAt AAA Life, we are building a future-focused team using AI and automation to transform life insurance operations. If you're driven by meaningful work and want to deliver solutions that matter to millions of members, this is your opportunity.We are seeking a Principal Machine Learning Engineer to serve as a technical leader within our Automation and AI organization. This role is accountable for defining and driving AI strategy, architecture, and delivery across multiple high-impact enterprise initiatives. The Principal MLE will lead the development of production-grade AI and agentic systems, ensuring successful deployment of business-critical solutions across Claims, Underwriting, and Member Services. These systems directly impact operational efficiency, decision quality, and customer experience at scale. This role requires deep expertise in modern AI, particularly in designing and deploying autonomous, agentic systems, an emerging and highly specialized area with a limited talent pool. This is a hands-on technical leadership role responsible for delivering enterprise-scale AI solutions where architectural decisions, system reliability, and model behavior have direct and measurable business impact.ResponsibilitiesPosition ResponsibilitiesEstablish engineering standards, best practices, and evaluation frameworks for AI systemsLead technical decision-making for model selection, system design, and deployment strategiesAct as the subject matter expert for agentic AI and modern LLM-based systems within the organizationArchitect and deliver production-grade, multi-step AI agents capable of autonomous reasoning, tool orchestration, task decomposition, memory management, and human-in-the-loop escalation-requiring specialized expertise in emerging agentic AI frameworksDesign and deliver AI systems on enterprise cloud platforms (e.g., AWS, Azure), including LLM services (AWS Bedrock, Azure OpenAI), supporting high-volume, business-critical workflows with strict requirements for reliability, auditability, and performanceOwn the agent evaluation and observability stack, including benchmarking, tracing, regression testing, and performance monitoringOptimize LLM inference costs and resource utilization for production workloadsPartner with business leaders to identify, prioritize, and shape AI-driven initiatives aligned with organizational goalsTranslate complex business problems into scalable AI solutions with measurable impactDrive roadmap planning and investment decisions related to AI and automationCollaborate with IT, data engineering, and operations teams to integrate AI solutions into enterprise systemsMentor and develop machine learning engineers and data scientistsProvide technical guidance and elevate team capabilities in modern AI practicesEnsure responsible and compliant use of AI systems, including managing risks related to model behavior, data usage, and regulatory considerations in a highly regulated industryLead evaluation and integration of external AI platforms and vendors, including assessment of cost, intellectual property, scalability, security, and long-term architectural impactCore Competencies Excellent communication skills and ability to explain ML results to non-technical audiencesProven ability to operate with a high degree of autonomy and accountabilityExperience driving adoption of AI solutions in enterprise environmentsAbility to influence technical direction and investment decisions across organizational boundariesTrack record of building engineering culture and raising the technical bar within a teamQualificationsEducation/Experience Master's degree (or higher) in Computer Science, Engineering, Statistics, or related quantitative field10+ years of hands-on experience in machine learning, AI, or related disciplines2+ years of recent experience architecting and delivering LLM-based and agentic AI systems in productionProven track record of delivering end-to-end AI solutions, from problem definition through production deploymentStrong programming skills in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)Preferred Qualifications Experience building agentic systems for document-heavy workflows (e.g., claims, underwriting, policy processing)Experience with enterprise cloud AI platforms (AWS Bedrock, SageMaker, Azure OpenAI)Experience with agent frameworks (LangGraph, LangChain, AutoGen, CrewAI, or equivalent)Experience with AI observability and evaluation tools (e.g., Langfuse, LangSmith, or similar)Familiarity with Model Context Protocol (MCP) or equivalent tool-integration standardsExperience deploying AI systems in regulated environments (insurance, finance, healthcare)Experience leading AI architecture across multiple teams or domainsEssential Job FunctionsWhile performing the duties of this job, the employee is frequently required to stand, walk, sit, use hands to finger, handle, or feel and talk or hear. Specific vision abilities required by this job include close vision, distance vision, color vision, depth perception, and ability to adjust focus.This job requires the ability to perform duties contained in the job description for this position, including, but not limited to, the above requirements. Reasonable accommodations will be made for otherwise qualified applicants as needed to enable them to fulfill these requirements.#LI-Remote