Senior AI Engineer

Posted Yesterday
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Gurgaon, Gurugram, Haryana, IND
In-Office
Senior level
eCommerce • Retail
The Role
Build and operate enterprise AI systems across the full lifecycle, including agentic workflows, RAG pipelines, model training and fine-tuning, AI observability, guardrails, and cloud-native deployment. Develop scalable AI services and React interfaces, manage production reliability and evaluation, contribute to architecture and code reviews, and mentor engineers using platforms such as GCP and Azure.
Summary Generated by Built In

About dunnhumby

dunnhumby is the global leader in Customer Data Science, helping the world's most ambitious retailers and brands put the customer at the heart of every decision. With nearly 3,000 experts across Europe, Asia, Africa and the Americas, we partner with iconic businesses like Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro to turn data into growth, innovation and measurable value for their customers.

Tech / Engineering

dunnhumby’s Technology and Engineering team builds the platforms, pipelines and systems that make customer data science possible at scale. From the data infrastructure that ingests billions of transactions to the APIs and cloud architecture that power our products, we engineer reliable, high-performance software trusted by the world’s leading retailers and brands.

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.

What You'll Do
  • 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.
What You'll Bring
  • 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.

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 your recruiter know what adjustments would help.

India Benefits

  • Healthcare & Family Cover: Group Medical Insurance of INR 500,000 for employees and dependents, plus dental and vision cover up to INR 5,000. 
  • Protection: Group Term Life Insurance and Group Personal Accident cover with benefit levels linked to employee grade, including disability benefits. 
  • Retirement & Wellbeing: Provident Fund, Gratuity, National Pension Scheme access, Indian Health Organisation membership, and confidential employee assistance support. 
  • Lifestyle & Flexibility: Office commute support, internet allowance of INR 2,000 per month for blended working, work-from-home kit support, subsidised food, and wellbeing resources. 
  • Recognition & Extras: Long service awards, Talent Scout referral programme, and family milestone support. 
  • Time Off & Family Leave: 25 days holiday plus 10 public holidays, paid maternity, paternity and adoption leave, and a day off for your birthday.

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)

Skills Required

  • Bachelor's or Master's degree in Computer Science, AI, Engineering, or a related field
  • 8+ years of software engineering experience
  • 3+ years building production AI/ML applications
  • Strong knowledge of distributed systems, cloud-native architecture, and microservices
  • Experience delivering enterprise-grade AI solutions from proof of concept to production
  • Expert-level Python programming
  • Experience with generative AI, LLMs, prompt engineering, embeddings, RAG, and agentic AI
  • Experience with model training, fine-tuning, experimentation, and hyperparameter optimization
  • Experience with cloud AI platforms, MLOps, containerization, Kubernetes, and infrastructure as code

dunnhumby Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dunnhumby and has not been reviewed or approved by dunnhumby.

  • Fair & Transparent Compensation — Pay is considered competitive relative to similar-sized firms in several markets. Positive perceptions of the overall pay-and-benefits mix support the view that compensation is broadly fair.
  • Leave & Time Off Breadth — Paid time off is described as generous, with multi‑week starting allowances plus extras like a paid birthday, loyalty‑based additional days, and periodic early Friday finishes. These features contribute to a favorable time‑off experience across several U.S. locations.
  • Healthcare Strength — Core coverage includes employer‑verified medical, dental, vision, life, and disability insurance alongside HSA/FSA options. This breadth of coverage is positioned as a solid component of the U.S. package.

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The Company
HQ: London
Year Founded: 1989

What We Do

Dunnhumby is a customer data platform that provides models and insights into how customers engage with retail and e-commerce spaces.

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