Principal Software Engineer

Overview As Principal Engineer, you will be the top technical authority for our customer-facing AI capabilities and cloud platform. You’ll define reference architectures for Generative and Agentic AI, set engineering standards, and deliver the highest-leverage components. You’ll shape direction across AI, data science, and platform teams through architecture reviews and hands-on mentorship. The role blends strategy with execution, operating across on-prem Oracle and AWS in a hybrid estate to scale AI across the marketing platform. This is an opportunity to lead transformative AI-enabled capabilities at scale. Compensation / Benefitswellness and benefits offeringstuition assistanceFlexible time offWork Your World program (work from anywhere)matching giftsflexible working arrangements ResponsibilitiesOwn end-to-end technical architecture for the AI platform, from data foundations to model serving and agent orchestrationDefine reference architectures, engineering standards, and paved-path patterns for AI and platform teamsMake and document build/buy decisions, model-selection, and platform strategy for leadershipLead design of new or enhanced AI capabilities aligned with business strategy and requirementsSet development environment, tooling, and AI-assisted engineering workflow standardsCollaborate with QA, product, data science, and production support to bring AI features to marketEstablish monitoring, cost-governance and reliability practices for production AI systemsGuide platform security and upgrade strategy for AI and cloud estateAct as principal technical authority on AI and cloud architecture across multiple teamsDevelop multi-quarter roadmaps and technical objectives for the AI platformAuthor reference architectures and technical design documentation for teams to execute againstProvide technical direction, review designs and code, and raise engineering standards for senior engineersPartner with QA to define test strategy and evaluation frameworks for AI systemsRecommend architecture and process improvements and communicate trade-offs to leadershipDevelop solutions in line with security/compliance requirements and shape policies as neededFacilitate design and rollout of new products/platform initiatives and inform executives of risks and alternativesLead RCA on complex incidents and coordinate cross-functional problem solvingIdentify and drive process improvements in engineering policies and proceduresChampion knowledge sharing through knowledge bases, reference designs, and case studiesContribute to end-to-end Application Development Lifecycle across teams Key requirements13+ years in ML engineering, data engineering, and large-scale distributed systems with deep architecture experience3+ years of hands-on production experience with Generative/Agentic AIProven ability to operate as a Principal-level IC guiding multiple teams without people managementTrack record as technical decision-maker on high-stakes platform and AI initiativesHands-on experience building and deploying production AI applications using large language models at scaleStrong data engineering skills: pipelines, transformations, and large datasetsExperience with distributed data processing (Spark/PySpark, Databricks) and orchestration (Airflow)Proficiency with ML lifecycle tooling (MLflow or equivalent)Experience with AWS production solutions (EC2, S3, EMR, Glue, Lambda, Redshift) and on-prem Oracle in a hybrid setupIaC and containerization (Terraform/CloudFormation, Docker, Kubernetes)Strong Python, Linux/Shell scripting, CI/CD, and software engineering fundamentalsAbility to write technical specifications and lead full software development lifecycleCollaborative, low-ego leadershipExcellent verbal and written communicationAnalytical problem-solving and proactive risk managementGenerative and Agentic AI design and deploymentRAG architectures, vector stores, embeddings, retrieval systemsAgentic AI: tool-using agents, orchestration, multi-step reasoning with guardrails