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Publicis Groupe

Runs advertising and digital transformation services

Principal Software Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeSan Diego, CA, USA$135.4k - $207.4k /yrIn-person

About the Job

Requirements

  • At least 13 years of experience across machine learning engineering, data engineering, and large-scale distributed systems, including deep architecture experience.
  • At least 3 years of hands-on experience designing and shipping Generative/Agentic AI systems in production.
  • Demonstrated ability to operate as a Principal-level individual contributor, setting technical direction, owning architecture, and influencing multiple teams without direct people-management authority.
  • A track record of being the technical decision-maker on high-stakes platform and AI initiatives.
  • Hands-on experience building and deploying production AI applications using large language models at scale.
  • Deep production experience with retrieval-augmented generation architectures, vector databases, embeddings, and retrieval systems, including chunking, indexing, and retrieval-quality optimization.
  • Experience designing agentic AI systems, including tool-using agents, orchestration, and multi-step reasoning workflows with appropriate guardrails and evaluation.
  • Expertise optimizing large language model usage across a platform, including model selection, prompt engineering, context strategy, fine-tuning where warranted, and inference/deployment optimization for cost and latency.
  • Ability to establish large language model operations and machine learning operations practices, including monitoring, observability, and evaluation frameworks for AI systems covering performance, cost management, and output-quality/guardrail metrics.
  • Active expert use of AI coding assistants such as Cursor, Claude Code, and GitHub Copilot, and spec-driven AI-assisted development in daily workflow; ability to set that standard for others.
  • Strong data engineering skills in pipeline design, data transformation, and working with large-scale datasets that feed AI systems, integrating existing infrastructure and building new pipelines where needed.
  • Depth with distributed data processing using Spark/PySpark, Databricks, and Hadoop/Hive; workflow orchestration with Airflow; and MLflow or equivalent for the machine learning lifecycle.
  • Ability to design and deploy retrieval-augmented generation systems, embeddings pipelines, and large-language-model-powered features on native Python infrastructure and/or Scikit-learn, XGBoost, PyTorch, TensorFlow, and FastAPI.
  • Ability to define and lead migration strategies from legacy systems to modern AI and cloud architecture.
  • Hands-on experience designing and deploying production-grade solutions on AWS, including compute and data services such as EC2, S3, EMR, Glue, Lambda, and Redshift, as well as on-premises Oracle in a hybrid estate.
  • Experience with infrastructure as code using Terraform or CloudFormation, containers and orchestration using Docker and Kubernetes, and secure multi-account cloud design covering identity and access management, network, and security boundaries.
  • Strong software engineering fundamentals in version control, testing, continuous integration/continuous delivery, and code review, and ability to set these standards for teams.
  • Proficiency in Python and Linux/Shell/bash scripting to automate processes.
  • Strong understanding of disaster recovery and business continuity solutions, performance tuning, and application monitoring/support of production applications with distributed teams.
  • Experience with scheduling applications with complex interdependencies, and reporting/report development on any reporting tool.
  • Ability to work independently and set direction while integrating with and elevating a team.
  • Proven analytical and problem-solving abilities, including the ability to anticipate and avoid problems before they occur.
  • Experience mentoring and technically guiding senior engineers, and comfort being the person others escalate the hardest problems to.
  • Experience working with geographically and culturally diverse teams.
  • Ability to write detailed technical specifications for developers, and to design, validate, and oversee software test strategy.
  • Deep familiarity with the full application development life cycle and ability to independently lead each phase.
  • Bachelor’s degree in Computer Science or equivalent.

Responsibilities

  • Own the end-to-end technical architecture for the AI platform, from data foundations through model serving, retrieval, and agent orchestration, and drive it from vision to production.
  • Define reference architectures, engineering standards, and paved-path patterns that AI and platform teams build against.
  • Make and document high-stakes build/buy, model-selection, and platform decisions concerning frameworks, vector stores, inference strategy, and cloud services; inform senior leadership of alternatives and trade-offs.
  • Lead analysis and design of new and enhanced AI capabilities for the marketing platform according to business strategy and requirements.
  • Set the standard for the development environment, tooling, and AI-assisted engineering workflow across teams.
  • Partner with QA, product, data science, and production support to bring new or enhanced AI features to market and resolve the most complex issues.
  • Establish monitoring, evaluation, cost-governance, and reliability practices for production AI systems.
  • Guide and de-risk platform, security, and version/patch upgrade strategy for the AI and cloud estate.
  • Act as the principal technical authority on AI and cloud architecture, driving alignment across developers, project managers, business analysts, data scientists, and business users on conceptualizing, estimating, and delivering applications and enhancements.
  • Own the definition of technical strategy and multi-quarter roadmaps for the AI platform, including scoping, sequencing, and realistic estimates for complex programs of work.
  • Lead the definition, development, and documentation of the platform’s technical objectives, architecture, and specifications in collaboration with internal users and departments.
  • Author reference architectures and technical design documentation defining system components, the development environment, and implementation strategy for teams to execute against.
  • Provide technical direction, review designs and code, and raise the engineering bar for Principal, Staff, and Senior engineers as a force multiplier rather than a people manager.
  • Partner with the QA organization to define test strategy, quality metrics, and evaluation frameworks for AI systems, and resolve questions about results.
  • Recommend and drive architecture and business-process improvements, and communicate problem/resolution processes to leadership.
  • Develop and implement solutions in accordance with policies, procedures, and security/compliance requirements, and shape those policies where they need to evolve.
  • Facilitate the design and implementation of new products and platform initiatives, informing senior executives of technical alternatives, risks, and trade-offs.
  • Set the standard for project and architecture documentation across the practice.
  • Lead root cause analysis on the most complex, cross-cutting incidents.
  • Work with cross-functional teams during critical incidents to assess, analyze, and resolve complex problems spanning multiple systems and teams.
  • Identify where existing engineering policies, standards, and procedures require improvement and drive the process-improvement effort.
  • Champion knowledge sharing by creating and improving Knowledge Base articles, reference designs, and case studies, and growing the technical maturity of the organization.

Desired Qualifications

  • Advanced degree or equivalent depth of experience.
  • Prior experience in automotive marketing and/or CRM applications.
  • Experience with ETL tooling such as Informatica or equivalent.
  • Proven ability to define solution architecture and set direction across teams.
  • Awareness of dimensional, fact, and data modelling with cube design and deployment experience related to data warehouse.
  • Familiarity with complex data lake environments spanning OLTP, MPP, and Hadoop platforms.
  • Excellence in impact analysis and root cause analysis.
  • Ability to design and build flexible, extensible systems focused on reuse, generation, and paved-path patterns for other teams.
  • Awareness of responsible AI, data privacy, and model-governance considerations for customer-facing systems.
  • Ability to work within tight deadlines and prioritize and execute effectively in a high-pressure environment.
  • Strong communication skills, verbal and written, including communicating technical strategy to non-technical audiences and all levels of management.
  • Strong analytical and problem-solving skills.
  • Ability to diagnose and troubleshoot problems quickly to maintain operational stability.
  • Motivation to learn new applications and domains, with an appetite for learning through exploration and reverse engineering.
  • Strong time-management skills and ability to take full ownership of ambiguous, high-impact problems.
  • A technical leader who elevates the team through interpersonal skills and a collaborative, low-ego approach.
  • Good verbal and written communication.
  • A can-do attitude and resilience to lead through challenges.

About the Company

Publicis Groupe

Runs advertising and digital transformation services

Publicis Groupe runs advertising, media buying and digital transformation services for companies that want to reach consumers, coordinate campaigns and improve their business systems. Its agency network includes creative and media specialists, while Publicis Sapient builds and modernizes the technology behind clients' operations. Epsilon adds customer data and marketing technology that connect brands with audiences and measure campaign results. Clients pay for consulting, campaign creation and execution, with production and media costs billed through alongside the group's service work. Founded in 1926, Publicis Groupe is headquartered in Paris, France.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1926

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