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Publicis Groupe

Runs advertising and digital transformation services

AI Technical Product Lead

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeHouston, TX, USA$160k - $210kIn-person

About the Job

Requirements

  • Experience operating at a senior Product Manager, AI Product Manager, Product Owner, or similar product leadership level in complex enterprise environments.
  • Demonstrated experience in renewable energy, solar, energy transition, utilities, or adjacent clean-energy markets, with an understanding of industry business models, operational workflows, data, assets, and technology ecosystems.
  • Proven experience taking AI, machine learning, advanced analytics, or data products from discovery and experimentation into production and measurable business adoption.
  • Strong AI and technical fluency, including comfort discussing machine learning and generative AI concepts, model lifecycle, data pipelines, cloud services, APIs, integrations, system architecture, MLOps, evaluation, monitoring, and technical dependencies; data scientist or software engineer experience is not required.
  • Ability to work with data scientists and engineers to define model and product requirements, challenge solution designs, ask meaningful technical questions, and translate technical implications into business impact and decision points.
  • Understanding of AI product evaluation, including offline and online metrics, benchmarks, experimentation, user feedback, operational KPIs, and business outcomes.
  • Working knowledge of responsible AI principles, data governance, privacy, security, explainability, model risk, and human-in-the-loop design.
  • Hands-on experience developing product strategies, roadmaps, business cases, requirements, user stories, acceptance criteria, process flows, and launch or adoption plans.
  • Experience working across multidisciplinary teams that may include renewable energy subject matter experts, operations, engineering, architecture, data science, data engineering, quality assurance, user experience/design, legal, security, and business stakeholders.
  • Proven ability to prioritize competing demands, manage ambiguity, facilitate decisions, and secure stakeholder alignment in a fast-evolving technology environment.
  • Ability to communicate credibly with senior business leaders and deeply technical teams through executive-level communication and storytelling.
  • Comfort working with financials, KPIs, product analytics, and value realization measures to guide prioritization and investment decisions.

Responsibilities

  • Partner with solar and renewable energy clients, product leaders, operators, data scientists, machine learning engineers, software engineers, architects, designers, and strategists to identify business problems that can be solved responsibly with AI.
  • Own the AI product vision, strategy, roadmap, and prioritized backlog for solutions supporting solar asset performance, generation forecasting, predictive maintenance, anomaly detection, energy trading and optimization, customer acquisition, project development, field operations, and grid integration.
  • Lead discovery across utility-scale, commercial and industrial, and distributed solar workflows, converting customer and operational needs into product hypotheses, epics, features, user stories, acceptance criteria, data requirements, model requirements, and non-functional requirements.
  • Evaluate where machine learning, generative AI, computer vision, forecasting, optimization, and intelligent automation can create measurable value, and distinguish AI opportunities from problems better solved through workflow, analytics, or platform improvements.
  • Collaborate directly with data science and engineering teams to define model objectives, training and inference data needs, evaluation metrics, human-in-the-loop workflows, integrations, APIs, cloud architecture, monitoring, and production-readiness requirements.
  • Drive AI product experimentation from problem framing and prototype development through pilot, validation, deployment, adoption, and continuous improvement.
  • Translate complex AI concepts, model outputs, uncertainty, limitations, and technical trade-offs into clear business decisions for senior client and operational stakeholders.
  • Define measurable product and model outcomes, including business value, user adoption, forecast accuracy, reliability, operational efficiency, model performance, safety, and responsible AI controls.
  • Build data and feedback strategies that improve product performance over time, including data quality, labeling, lineage, access, governance, model monitoring, drift detection, and retraining considerations.
  • Embed responsible AI and product risk management throughout the lifecycle, addressing explainability, privacy, security, bias, reliability, regulatory considerations, and appropriate human oversight.
  • Facilitate product discovery, roadmap, technical design, model review, and stakeholder decision sessions across product, data, engineering, architecture, user experience, operations, commercial, and client teams.
  • Build trusted relationships with senior renewable energy stakeholders and influence investment, prioritization, and adoption decisions without formal authority.

Desired Qualifications

  • Experience with solar development, photovoltaic asset management, energy forecasting, distributed energy resources, battery energy storage, virtual power plants, energy markets, grid operations, or renewable energy trading.
  • Experience developing AI use cases involving time-series forecasting, predictive maintenance, anomaly detection, optimization, computer vision, geospatial data, digital twins, or generative AI for renewable energy workflows.
  • Familiarity with renewable energy and solar data sources and platforms, such as supervisory control and data acquisition (SCADA), weather data, irradiance data, smart-meter data, asset performance management systems, geographic information systems (GIS), market data, and energy management systems.
  • Experience with cloud AI/data ecosystems such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud, and modern MLOps, analytics, and data-platform practices.
  • Prior consulting experience delivering AI-enabled or technology-enabled transformation for energy, utilities, or renewable energy clients.
  • AI product management, cloud, product, or Agile certification, such as Certified Scrum Product Owner (CSPO) or SAFe Product Owner/Product Manager.

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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