Software Engineer - Data Science & AI

About Euromonitor

Euromonitor International leads the world in data analytics and research into markets, industries, economies and consumers. We provide truly global insight and data on thousands of products and services; we are the first destination for organisations seeking growth. With our guidance, our clients can make bold, strategic decisions with confidence.

Overview of the role

Passport, Euromonitor's flagship platform, has just been rebuilt from the ground up. It is the largest technology investment in the company's history, and AI now sits at the core of the system. 

Euromonitor is establishing an AI and Data Science team in India to lead this work. The remit is a framework driven, platform centric approach: the team builds the AI platform, reusable agents, skills and tooling that product teams use to engineer AI and Data Science capability into Passport and other customer offerings, including new products built on AI and agentic flows. 

Based in Bengaluru and reporting to the Technical Lead, this early career role suits an engineer with strong software fundamentals and hands-on enthusiasm for modern AI engineering. The weight of the role is AI and backend engineering: building and operating the services, APIs and agentic components of the platform under the guidance of senior and lead engineers, with growing exposure to the data science methods the platform packages, such as ranking, retrieval quality and evaluation. Everything you build ships as reusable components adopted by product teams, not features inside a single product. 

What you’ll do

AI and Backend Engineering 

• Build and maintain backend services, APIs and agentic components of the AI platform, following the team's standards for versioning, documentation and multi-consumer design. 

• Implement RAG and retrieval features: data ingestion, chunking and indexing pipelines, and search integration, using the team's shared services. 

• Contribute to the agent framework, the skills and tool registry, and the reference implementations that consuming teams start from. 

• Instrument everything you ship: logging, tracing, cost and token telemetry, and automated tests as part of the definition of done. 

Applied Data Science (supporting) 

• Support evaluation work: preparing golden datasets, running LLM-as-judge pipelines and regression suites, and reporting quality results. 

• Assist with experiments on ranking, retrieval and prompt changes, learning the statistical methods behind them from senior colleagues. 

Learning and Collaboration 

• Grow through design reviews, pairing and mentorship from senior and lead engineers, taking on components of increasing scope over time. 

• Document what you build and help consuming teams use it; adoption is part of everyone's job on this team. 

Requirements

What we’re looking for

Essential 

• 3 -6 years of software engineering experience, or strong internship and project evidence, with solid fundamentals in data structures, API development and testing. 

• Strong Python and working SQL, with clean, reviewable coding habits. 

• Hands-on experience with LLM APIs and modern Generative AI building blocks: prompting, RAG basics, and at least one orchestration framework such as LangGraph, LangChain or LlamaIndex (LangGraph and LangChain preferred), from work, internships or substantial personal projects. 

• Familiarity with cloud fundamentals on Azure, AWS or GCP and with containers (Azure preferred). 

• Foundations in Machine Learning concepts: embeddings, evaluation metrics, and the basics of ranking or NLP. 

• Curiosity and clear communication: the ability to ask good questions, take feedback well and explain what you built and why. 

Desirable Experience 

• Exposure to a typed backend language such as C#, Java, Go or TypeScript (C# and .NET preferred, reflecting the services you will integrate with). 

• Vector or hybrid search exposure such as Elasticsearch, pgvector or Azure AI Search. 

• Kubernetes basics and CI/CD tooling such as GitHub Actions or Azure DevOps. 

• Evaluation or observability tooling for LLM workloads such as Ragas, DeepEval, promptfoo, LangSmith or Langfuse. 

• Open source contributions, hackathon results or published personal projects that show initiative. 

• Coursework or projects in information retrieval, recommender systems or NLP. 

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Benefits

Why work for Euromonitor?

Our Values:

We seek individuals who act with  integrity

We look for candidates who are  curious about the world

We feel that as a community, we’re stronger  together

We seek to enable people to feel  empowered

We welcome candidates who bring strength in  diversity

International: We have a multinational workforce and communicate daily across our 16 global offices.

Hardworking and Sociable: Our staff balance hard work with enjoyment, offering flexible hours and regular social events, including after-work meetups, summer and Christmas parties.

Committed to Making a Difference: Our Corporate Social Responsibility Programme provides two volunteering days annually; donation amounts for new starters and supports local and international charities through various initiatives.

Excellent Benefits: We offer competitive salaries, private health insurance, and generous holiday allowances, amongst much more!

Opportunities to Grow: We provide extensive training and development, promoting from within and across departments, and rewarding talent.

Equal Employment Opportunity: Euromonitor International does not discriminate based on race, colour, religion, sex, national origin, political affiliation, sexual orientation, gender identity, marital status, disability, genetic information, age, membership in an employee organization, or other non-merit factors.