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Mondelez International

Makes cookies, chocolate, gum and candy worldwide

Full Stack Developer - AI Reporting & Insights

AI Application Engineering +1Updated on Nov 13
Full-timeNo salary listed

About the Job

Requirements

  • Experience working collaboratively with multiple vendors.
  • Experience leading complex projects and applying project management.
  • Stakeholder management and influencing skills.
  • Experience managing infrastructure services delivery, support, and excellence.
  • Experience working in a global IT function with regional or global responsibilities.
  • Experience working with IT outsourcing providers using frameworks such as the Information Technology Infrastructure Library.
  • Experience working with internal and external teams and leading when necessary.
  • Strong proficiency in Python and experience building production-grade applications or pipelines.
  • Experience in at least one of full stack development, artificial intelligence and machine learning engineering, or data engineering, with willingness to broaden across the other disciplines.
  • Hands-on experience with cloud platforms, particularly Amazon Web Services, and familiarity with Databricks, Spark, Delta Lake, and Unity Catalog.
  • Exposure to large language models and generative AI, including model integration, prompt engineering, retrieval-augmented generation pipelines, or agent-based architectures.
  • Familiarity with modern web frameworks such as React and Next.js, and application programming interface design using REST or GraphQL.
  • Understanding of data modelling, extract-transform-load and extract-load-transform processes, and working with structured and unstructured data at scale.
  • Solid software engineering fundamentals, including version control with Git, testing, continuous integration and continuous delivery, containerisation with Docker, and infrastructure as code with Terraform.
  • Ability to communicate technical trade-offs to non-technical stakeholders and work in a cross-functional team.

Responsibilities

  • Build and ship full stack applications, including application programming interfaces, backend services, and front-end interfaces, to present AI-generated insights to business users using Python, React/Next.js, and cloud-native services.
  • Design, build, and maintain data pipelines that ingest, transform, and serve market and business data using Python, Databricks, Delta Lake, Spark, and AWS services.
  • Develop and deploy AI/ML models and large-language-model workflows, including retrieval-augmented generation, prompt engineering, and agent orchestration using frameworks such as LangChain or LangGraph.
  • Implement monitoring, logging, and alerting for pipelines, models, and applications to ensure reliability, performance, and cost-efficiency in production.
  • Collaborate with Product, Data Science, and Business stakeholders to translate requirements into technical designs, user stories, and working software.
  • Contribute to platform architecture decisions, including infrastructure as code with Terraform, containerisation, and continuous integration and delivery practices.
  • Write clean, tested, and well-documented code; participate in code reviews and sprint ceremonies; and share knowledge across the team.
  • Provide software and application knowledge to support implementation of solutions.
  • Ensure delivered services are optimized to meet business demands and the service operations strategy; plan, measure, report, and communicate service improvement initiatives; and consult on issues and resolutions.
  • Recommend actions to optimize investments and benefits and mitigate risks.
  • Identify and evaluate suppliers, onboard new vendors, and establish and run vendor governance.
  • Collaborate with management and follow up on requisitions, purchase orders, invoices, and payments.
  • Work with project resources to provide design collateral and configure software components in alignment with security policy and governance.
  • Ensure adherence to development and configuration standards and processes.

Desired Qualifications

  • Experience with agent orchestration frameworks such as LangChain, LangGraph, AutoGen, or CrewAI.
  • Familiarity with the Databricks ecosystem, including MLflow, Feature Store, or Genie.
  • Exposure to natural language processing or multimodal artificial intelligence.
  • Experience with monitoring and observability tools such as Prometheus, Grafana, or CloudWatch.
  • Knowledge of security best practices in cloud and AI infrastructure.
  • Prior experience in a consumer packaged goods or fast-moving consumer goods environment, or working with syndicated market data such as Nielsen, Circana/IRI, or Kantar.
  • Intellectual curiosity and a bias for learning and staying current with the fast-moving AI/ML landscape.

About the Company

Mondelez International

Makes cookies, chocolate, gum and candy worldwide

Mondelez International makes snack foods sold in grocery stores, convenience shops and online from North America and Europe to Latin America, Asia and Africa. Its brands include Oreo and Chips Ahoy cookies, Cadbury, Milka and Toblerone chocolate, Trident gum and Halls cough drops. The company runs factories around the world, buys large amounts of cocoa and wheat, and ships finished snacks to retailers and distributors. It earns money by selling these branded snacks at wholesale, and it grows by adding local brands and buying regional bakeries and snack makers. Mondelez took its current name in 2012, when Kraft Foods split off its North American grocery business, and is based in Chicago.

Company size
10,001+
Company stage
IPO
Headquarters
Chicago, IL
Founded
1903

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