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Salary
$27k – $68k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Senior · 8+ years exp
Overview
Company
Impact
Profile match
Dunnhumby is a customer data science company that provides analytics, personalization platforms, and retail media solutions for global brands and retailers. Headquartered in London, United Kingdom, the enterprise operates as a wholly owned subsidiary of the retail giant Tesco. By leveraging consumer purchase insights and behavioral algorithms, it helps client organizations optimize pricing strategies, loyalty programs, and targeted marketing campaigns.

dunnhumby is the global leader in Customer Data Science, partnering with the world’s most ambitious retailers and brands to put the customer at the heart of every decision. We combine deep insight, advanced technology, and close collaboration to help our clients grow, innovate, and deliver measurable value for their customers. 

dunnhumbyemploys nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Nestlé, Unilever and Metro.

We're looking for a Senior AI Engineer to help build and scale dunnhumby's Enterprise AI Platform- designing, deploying, and operating production grade AI systems used across engineering teams. You'll work across the full AI lifecycle: model training and fine-tuning, agentic workflows, RAG, AI observability, and AI-powered user experiences, using the latest advancements in Generative AI.

Key Responsibilities

  • Build reusable, scalable AI services for prompt orchestration, model routing, embeddings, structured generation, and tool calling; develop configurable multi-provider AI runtimes and secure cloud-native microservices.
  • Design multi-agent and autonomous systems with reasoning, planning, memory, and tool execution; build graph-based, long-running workflows with human-in-the-loop checkpoints using MCP and A2A.
  • Build enterprise-grade RAG pipelines- ingestion, chunking, embeddings, hybrid search, reranking, citations - and continuously evaluate retrieval quality.
  • Train, fine tune (LoRA/QLoRA/PEFT), and evaluate ML/DL models; build training pipelines, run experimentation and hyperparameter optimization, and productionize models with data science partners.
  • Deploy, monitor, and continuously improve agents and models in production - experiment tracking, model registry, versioning/rollback, drift and cost monitoring, CI/CD, and canary/blue-green deployments.
  • Implement guardrails for hallucination, prompt injection, and PII; establish evaluation, monitoring, and responsible-AI compliance practices.
  • Build and deploy cloud-native AI services (Docker, Kubernetes, Terraform) on GCP and Azure with autoscaling, observability, and distributed tracing; own services from build through production support.
  • Build responsive React-based interfaces for chat, copilots, prompt playgrounds, and agent/evaluation dashboards, integrated via REST, SSE, and WebSockets.
  • Write clean, tested code; drive architecture reviews, code reviews, and mentor engineers.

Required Qualifications

  • Bachelor's/Master's in Computer Science, AI, Engineering, or related field.
  • 8+ years of software engineering experience, including 3+ years building production AI/ML applications.
  • Strong grounding in distributed systems, cloud-native architecture, and microservices.
  • Track record delivering enterprise-grade AI solutions from POC to production.

Technical Skills

Programming: Python (expert), TypeScript/JavaScript, SQL, async programming, REST & gRPC, design patterns

AI/ML Concepts: LLMs, prompt engineering, embeddings, RAG, hybrid search, agentic AI (tool/function calling, MCP, A2A), model training & fine-tuning (LoRA/QLoRA/PEFT), hyperparameter optimization, GPU optimization, quantization

AI Frameworks: LangChain, LangGraph, Google ADK, OpenAI Agents SDK, CrewAI, AutoGen, LlamaIndex, Semantic Kernel, DSPy, Pydantic AI

Cloud AI Platforms: Google Vertex AI, Azure AI Foundry, Azure OpenAI, Model Garden

ML & MLOps: PyTorch, TensorFlow, Hugging Face, MLflow, Kubeflow, model registry, experiment tracking, continuous training

AgentOps & Observability: LangSmith/Langfuse/Arize Phoenix, OpenTelemetry, Grafana, New Relic, agent evaluation, cost monitoring

Vector Databases: Pinecone/Weaviate/Milvus/pgvector/Vertex AI Vector Search/Azure AI Search

Cloud & DevOps: Docker, Kubernetes, Terraform, ArgoCD, GitHub Actions/Azure DevOps, CI/CD, IaC

Workflow Orchestration: Temporal/Argo Workflows/event-driven architecture/message queues

What you can expect from us

We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not expect.  Plus, thoughtful perks, like flexible working hours and your birthday off.

You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.

And we don’t just talk about diversity and inclusion. We live it every day - with thriving networks including dh Gender Equality Network, dh Proud, dh Family, dh One, dh Enabled and dh Thrive as the living proof.  We want everyone to have the opportunity to shine and perform at your best throughout our recruitment process. Please let us know how we can make this process work best for you. 

Our approach to Flexible Working

At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.

We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.

For further information about how we collect and use your personal information please see our Privacy Notice which can be found (here)

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