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NielsenIQ

Global provider of consumer purchasing data

Lead AI & Automation Developer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeMumbai, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Engineering, or a related field is required; a Master's degree is a plus.
  • At least 5 years of relevant experience in software development, automation engineering, data engineering, analytics engineering, AI solutions, or a comparable technical role.
  • Demonstrated experience delivering automation or AI solutions into production and supporting them after release.
  • Strong hands-on proficiency in Python, including object-oriented programming, data processing, reusable package design, and maintainable coding practices.
  • Practical experience building applications or automations using Large Language Models, including prompt design, grounding, evaluation, and safe use of model outputs.
  • Experience with structured and unstructured data, data modeling, SQL, and Python data libraries such as Pandas or Polars.
  • Experience designing and consuming REST APIs and integrating multiple systems and data sources.
  • Ability to automate legacy reports and operational processes while preserving business rules, controls, quality, and auditability.
  • Experience with Git, code reviews, testing frameworks such as Pytest, CI/CD practices, logging, exception handling, and production support.
  • Working knowledge of cloud-based solutions, preferably Microsoft Azure, and enterprise AI services such as Azure OpenAI.
  • Strong analytical, debugging, and problem-solving skills, with the ability to convert ambiguous business needs into practical solutions.
  • Clear stakeholder communication, documentation, ownership, and prioritization skills.

Responsibilities

  • Understand existing Innovation reports and processes and partner with stakeholders to identify pain points, repetitive activities, quality issues, and automation opportunities.
  • Identify and prioritize automation opportunities based on business value, feasibility, risk, and reuse potential.
  • Translate business requirements into practical technical solutions and clear delivery plans.
  • Develop Python-based automations, data-processing workflows, APIs, and scheduled solutions for legacy reports and processes.
  • Build LLM-powered solutions for use cases such as extraction, summarization, classification, knowledge retrieval, and recommendation generation.
  • Integrate solutions with existing tools, files, databases, APIs, and cloud services while maintaining quality, security, and auditability.
  • Deploy, document, monitor, and support solutions in production, and create reusable components that can be scaled across ARC.
  • Work with stakeholders to drive adoption and measure improvements in effort, cycle time, quality, and reliability.

Desired Qualifications

  • Experience with RAG, vector databases, semantic search, LangChain, or comparable orchestration frameworks.
  • Experience with workflow and low-code automation platforms such as Power Automate, and analytics tools such as Power BI.
  • Familiarity with Infrastructure as Code tools such as Terraform or Pulumi.
  • Knowledge of SQL and NoSQL databases, distributed systems, microservices, and event-driven architecture.
  • Exposure to Docker, Kubernetes, infrastructure as code, and observability tools.
  • Experience with AI-assisted development tools such as GitHub Copilot and Agile/Scrum delivery practices.
  • Familiarity with responsible AI, privacy, access controls, data governance, and security requirements in enterprise environments.

About the Company

NielsenIQ

Global provider of consumer purchasing data

NielsenIQ collects and analyzes consumer purchasing data to help retailers and brands understand market behavior. It tracks what people buy, when, and where, using this data to measure market share and purchasing trends across categories. The product works by aggregating point-of-sale and other consumer data, then turning it into actionable insights and benchmarks that clients can use to optimize pricing, assortment, promotions, and marketing. NielsenIQ differentiates itself through its long history (dating back to 1923) and a broad global footprint (operating in over 100 countries), plus its expanded capabilities after merging with GfK in 2023 to strengthen data on technology and durable goods. Its goal is to provide objective, data-driven guidance that helps retailers and brands make informed decisions and improve performance.

Company size
10,001+
Company stage
IPO
Headquarters
Chicago, IL
Founded
1923

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