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Open nowPosted 8 hours ago

Senior Software Engineer - Data Science & AI

Workable (global search)106,934 open roles

Where
Bengaluru, KA, India
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Your applicationOpen nowSenior Software Engineer - Data Science & AIWorkable (global search) · Bengaluru, KA, India

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8.5% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 4 days.

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  5. 34.1%30 days
This job: posted 8 hours ago

Workable (global search) median: 4 days open

The posting

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 role suits a senior engineer whose centre of gravity is applied Data Science and AI (ranking, retrieval and evaluation), combined with the backend software engineering competence to ship that work as reusable, production grade services that other teams build on. Reusability is the defining measure of the role: success is components adopted across product teams, not features shipped into a single product.

What you’ll do

Applied Data Science and AI

  • Develop reusable ranking, personalisation and recommendation components, taking them from experimentation through to shared services with measurable quality baselines.
  • Build and operate the evaluation harness as a shared service: golden dataset curation, LLM-as-judge pipelines, regression gates in CI, and quality metrics that consuming teams adopt.
  • Advance the shared retrieval capability across structured and unstructured data: chunking and indexing strategies, hybrid search, reranking and embedding lifecycle.
  • Bring statistical rigour to the platform: experiment design, judge calibration and the interpretation of quality deltas, so decisions about models and components rest on evidence.

Reusable Platform Services

  • Design and build backend services and APIs for the AI platform (retrieval, ranking, evaluation and agentic components) as versioned, documented, multi-consumer services rather than product embedded code.
  • Contribute to the agent framework and skills and tool registry, with clean SDK surfaces, backward compatibility and abstraction discipline suitable for consumption by multiple product teams.
  • Build for production from the start: observability, cost and token telemetry, quality gates and Responsible AI controls embedded in every component.

Collaboration and Enablement

  • Onboard consuming teams onto platform components through reference implementations, documentation and paved road patterns; treat adoption as a first class outcome of every piece of work.
  • Work with Engineering, Architecture and Data Platform teams to keep platform services aligned with Euromonitor's cloud native architecture.
  • Raise the bar on engineering practice within the team through design reviews, testing standards and mentoring as the team grows.

Requirements

What we’re looking for

Essential

  • 7+ years across Data Science and software engineering, with deep applied Data Science: Machine Learning fundamentals, ranking, recommendation or NLP experience, and the statistical grounding to design and interpret evaluations.
  • A proven track record of building AI and Data Science functionality as reusable services, libraries or components adopted by multiple teams, with evidence of that adoption, rather than solely features inside a single product.
  • Hands-on depth in modern Generative AI engineering: RAG and retrieval systems; LLM orchestration frameworks such as LangGraph, LangChain, LlamaIndex or Semantic Kernel (LangGraph and LangChain preferred); prompt and evaluation tooling; and vector or hybrid search such as Elasticsearch, OpenSearch, Azure AI Search, pgvector or a dedicated vector database (Elasticsearch preferred).
  • Strong backend engineering competence: API and service design, data pipelines, and production operations on a major cloud platform such as Azure, AWS or GCP, with container orchestration on Kubernetes (Azure and AKS preferred).
  • Strong Python, plus working competence in at least one further backend language such as C#, Java, Go or TypeScript (C# and .NET preferred, reflecting the services you will integrate with).
  • Evidence of production rigour: observability and tracing for LLM workloads (OpenTelemetry, LangSmith, Langfuse or similar), automated testing, CI/CD (Azure DevOps or GitHub Actions preferred) and cost awareness.
  • The ability to explain technical approaches, trade-offs, limitations and results clearly to engineers, product owners and other stakeholders; adoption of platform components depends on it.

Desirable Experience

  • Experience with MCP or tool calling protocols, agent runtimes, or LLM gateway patterns such as routing, caching and fallback.
  • LLM-as-judge calibration, golden dataset methodology or online experimentation experience, including evaluation frameworks such as Ragas, DeepEval or promptfoo.
  • Model development experience with PyTorch, TensorFlow or scikit-learn, including training or fine tuning beyond API level usage of foundation models.
  • Exposure to adjacent agent ecosystems and platforms such as AutoGen, CrewAI, OpenAI Agents SDK, or MLOps tooling such as MLflow, Azure Machine Learning, SageMaker or Vertex AI.
  • Contribution to internal platforms, open source libraries or SDKs with real external consumers.
  • Experience in information retrieval or search relevance at scale.
  • Background in market research, publishing, information services or another accuracy-sensitive domain.

#LI-HYBRID

#LI-RP1

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.

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